{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script><script>requirejs.config({paths: { 'plotly': ['https://cdn.plot.ly/plotly-latest.min']},});if(!window._Plotly) {require(['plotly'],function(plotly) {window._Plotly=plotly;});}</script>"
      ]
     },
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "#%matplotlib inline\n",
    "import pickle as pk\n",
    "import csv\n",
    "import datetime\n",
    "import lightgbm as lgb\n",
    "from scipy import stats\n",
    "from scipy.sparse import hstack, csr_matrix\n",
    "from sklearn.model_selection import train_test_split\n",
    "from wordcloud import WordCloud\n",
    "from collections import Counter\n",
    "\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn import preprocessing\n",
    "from sklearn.cross_validation import train_test_split\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import classification_report\n",
    "import plotly.offline as py\n",
    "py.init_notebook_mode(connected=True)\n",
    "import plotly.graph_objs as go\n",
    "import plotly.tools as tls\n",
    "\n",
    "#from xgboost import XGBClassifier\n",
    "import lightgbm as lgb\n",
    "from sklearn import model_selection\n",
    "from sklearn.metrics import accuracy_score\n",
    "import re\n",
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_X_tr = pd.read_csv('D:/transaction_risk_competition/transaction_train_new.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>UID</th>\n",
       "      <th>channel</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>trans_amt</th>\n",
       "      <th>amt_src1</th>\n",
       "      <th>merchant</th>\n",
       "      <th>code1</th>\n",
       "      <th>code2</th>\n",
       "      <th>trans_type1</th>\n",
       "      <th>...</th>\n",
       "      <th>ip1</th>\n",
       "      <th>bal</th>\n",
       "      <th>amt_src2</th>\n",
       "      <th>acc_id2</th>\n",
       "      <th>acc_id3</th>\n",
       "      <th>geo_code</th>\n",
       "      <th>trans_type2</th>\n",
       "      <th>market_code</th>\n",
       "      <th>market_type</th>\n",
       "      <th>ip1_sub</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19092</td>\n",
       "      <td>102</td>\n",
       "      <td>30</td>\n",
       "      <td>11:48:47</td>\n",
       "      <td>1459</td>\n",
       "      <td>acdbdb842ac20f1e</td>\n",
       "      <td>abc6bc660561e0eb</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>26bcf43a19df14c8</td>\n",
       "      <td>...</td>\n",
       "      <td>a664530c1fb20abe</td>\n",
       "      <td>1007</td>\n",
       "      <td>9fefed0a981dcb7a</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>wsbq</td>\n",
       "      <td>102.0</td>\n",
       "      <td>2ecf94369847c748</td>\n",
       "      <td>1.0</td>\n",
       "      <td>45f4ca1f4e9b9cb7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>13465</td>\n",
       "      <td>140</td>\n",
       "      <td>23</td>\n",
       "      <td>16:58:03</td>\n",
       "      <td>725</td>\n",
       "      <td>4d7831c6f695ab19</td>\n",
       "      <td>7a87b1aa20972d48</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>...</td>\n",
       "      <td>52abe1e300a8aa10</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>wte7</td>\n",
       "      <td>105.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2b416f1d7e89ad3b</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>13713</td>\n",
       "      <td>140</td>\n",
       "      <td>22</td>\n",
       "      <td>09:56:39</td>\n",
       "      <td>127</td>\n",
       "      <td>c5fc631370cabc0d</td>\n",
       "      <td>cfd035fc7e0a53b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>...</td>\n",
       "      <td>e4c132d02ff6c095</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ws7n</td>\n",
       "      <td>105.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ff71a556d86c4b8f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>22703</td>\n",
       "      <td>140</td>\n",
       "      <td>1</td>\n",
       "      <td>18:11:45</td>\n",
       "      <td>99317</td>\n",
       "      <td>a571c7fda8b7df37</td>\n",
       "      <td>c71c876b8979028e</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>...</td>\n",
       "      <td>e1c78a56cc9dfc8b</td>\n",
       "      <td>100</td>\n",
       "      <td>fbf6bf3c8927414c</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>wqj6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>cf1527a0b4173e8f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>17816</td>\n",
       "      <td>140</td>\n",
       "      <td>22</td>\n",
       "      <td>13:04:02</td>\n",
       "      <td>3361</td>\n",
       "      <td>c5fc631370cabc0d</td>\n",
       "      <td>6628f5ca013e3582</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>...</td>\n",
       "      <td>abb6b4b8f15be6d6</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>105.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>cbc62c2b1cb7deb9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>12037</td>\n",
       "      <td>102</td>\n",
       "      <td>8</td>\n",
       "      <td>01:09:29</td>\n",
       "      <td>5536</td>\n",
       "      <td>d7de70fc65292e41</td>\n",
       "      <td>3f6d3d0f42519ea4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6d55c54c8b1056fb</td>\n",
       "      <td>...</td>\n",
       "      <td>35d6ccb3b4ff776a</td>\n",
       "      <td>100</td>\n",
       "      <td>079946f395cc0cf1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>wwhu</td>\n",
       "      <td>102.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1488e4c1cc8f1c55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>18983</td>\n",
       "      <td>140</td>\n",
       "      <td>10</td>\n",
       "      <td>10:31:27</td>\n",
       "      <td>135470</td>\n",
       "      <td>27c42480134c0d02</td>\n",
       "      <td>7c805cb2868bb52b</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>...</td>\n",
       "      <td>26958916ef8a31c4</td>\n",
       "      <td>100</td>\n",
       "      <td>c82bae1f6ebe5674</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>wtbx</td>\n",
       "      <td>105.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>597d295ddce706f7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>12741</td>\n",
       "      <td>140</td>\n",
       "      <td>23</td>\n",
       "      <td>11:56:18</td>\n",
       "      <td>1459</td>\n",
       "      <td>f29829bc82459191</td>\n",
       "      <td>d11d91b96fe7a2ef</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>...</td>\n",
       "      <td>01cb473697bc732e</td>\n",
       "      <td>100</td>\n",
       "      <td>9a8ee16bde15e38a</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>wtkn</td>\n",
       "      <td>105.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9d3961d2ea1944fc</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>15986</td>\n",
       "      <td>102</td>\n",
       "      <td>1</td>\n",
       "      <td>06:53:27</td>\n",
       "      <td>24020</td>\n",
       "      <td>155c9e1c32bd0fa2</td>\n",
       "      <td>3bd5cf7c40962299</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>61bfb66c928f36ac</td>\n",
       "      <td>...</td>\n",
       "      <td>b2c59b4bfd512cd1</td>\n",
       "      <td>100</td>\n",
       "      <td>cf6e3a074407c379</td>\n",
       "      <td>01092023fb4f373d</td>\n",
       "      <td>99b877d5d88e8478</td>\n",
       "      <td>wtq6</td>\n",
       "      <td>102.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>80e715671282e957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10057</td>\n",
       "      <td>102</td>\n",
       "      <td>26</td>\n",
       "      <td>14:14:13</td>\n",
       "      <td>8798</td>\n",
       "      <td>155c9e1c32bd0fa2</td>\n",
       "      <td>d8babe2d19fa0c08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6d55c54c8b1056fb</td>\n",
       "      <td>...</td>\n",
       "      <td>aa0a0b28ce6c1757</td>\n",
       "      <td>192</td>\n",
       "      <td>9fefed0a981dcb7a</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>wxrv</td>\n",
       "      <td>102.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3fa05a459ddaa70d</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     UID  channel  day      time  trans_amt          amt_src1  \\\n",
       "0  19092      102   30  11:48:47       1459  acdbdb842ac20f1e   \n",
       "1  13465      140   23  16:58:03        725  4d7831c6f695ab19   \n",
       "2  13713      140   22  09:56:39        127  c5fc631370cabc0d   \n",
       "3  22703      140    1  18:11:45      99317  a571c7fda8b7df37   \n",
       "4  17816      140   22  13:04:02       3361  c5fc631370cabc0d   \n",
       "5  12037      102    8  01:09:29       5536  d7de70fc65292e41   \n",
       "6  18983      140   10  10:31:27     135470  27c42480134c0d02   \n",
       "7  12741      140   23  11:56:18       1459  f29829bc82459191   \n",
       "8  15986      102    1  06:53:27      24020  155c9e1c32bd0fa2   \n",
       "9  10057      102   26  14:14:13       8798  155c9e1c32bd0fa2   \n",
       "\n",
       "           merchant code1 code2       trans_type1        ...         \\\n",
       "0  abc6bc660561e0eb   NaN   NaN  26bcf43a19df14c8        ...          \n",
       "1  7a87b1aa20972d48   NaN   NaN  c2f2023d279665b2        ...          \n",
       "2  cfd035fc7e0a53b2   NaN   NaN  c2f2023d279665b2        ...          \n",
       "3  c71c876b8979028e   NaN   NaN  c2f2023d279665b2        ...          \n",
       "4  6628f5ca013e3582   NaN   NaN  c2f2023d279665b2        ...          \n",
       "5  3f6d3d0f42519ea4   NaN   NaN  6d55c54c8b1056fb        ...          \n",
       "6  7c805cb2868bb52b   NaN   NaN  c2f2023d279665b2        ...          \n",
       "7  d11d91b96fe7a2ef   NaN   NaN  c2f2023d279665b2        ...          \n",
       "8  3bd5cf7c40962299   NaN   NaN  61bfb66c928f36ac        ...          \n",
       "9  d8babe2d19fa0c08   NaN   NaN  6d55c54c8b1056fb        ...          \n",
       "\n",
       "                ip1   bal          amt_src2           acc_id2  \\\n",
       "0  a664530c1fb20abe  1007  9fefed0a981dcb7a               NaN   \n",
       "1  52abe1e300a8aa10   100               NaN               NaN   \n",
       "2  e4c132d02ff6c095   100               NaN               NaN   \n",
       "3  e1c78a56cc9dfc8b   100  fbf6bf3c8927414c               NaN   \n",
       "4  abb6b4b8f15be6d6   100               NaN               NaN   \n",
       "5  35d6ccb3b4ff776a   100  079946f395cc0cf1               NaN   \n",
       "6  26958916ef8a31c4   100  c82bae1f6ebe5674               NaN   \n",
       "7  01cb473697bc732e   100  9a8ee16bde15e38a               NaN   \n",
       "8  b2c59b4bfd512cd1   100  cf6e3a074407c379  01092023fb4f373d   \n",
       "9  aa0a0b28ce6c1757   192  9fefed0a981dcb7a               NaN   \n",
       "\n",
       "            acc_id3 geo_code trans_type2       market_code  market_type  \\\n",
       "0               NaN     wsbq       102.0  2ecf94369847c748          1.0   \n",
       "1               NaN     wte7       105.0               NaN          NaN   \n",
       "2               NaN     ws7n       105.0               NaN          NaN   \n",
       "3               NaN     wqj6         NaN               NaN          NaN   \n",
       "4               NaN      NaN       105.0               NaN          NaN   \n",
       "5               NaN     wwhu       102.0               NaN          NaN   \n",
       "6               NaN     wtbx       105.0               NaN          NaN   \n",
       "7               NaN     wtkn       105.0               NaN          NaN   \n",
       "8  99b877d5d88e8478     wtq6       102.0               NaN          NaN   \n",
       "9               NaN     wxrv       102.0               NaN          NaN   \n",
       "\n",
       "            ip1_sub  \n",
       "0  45f4ca1f4e9b9cb7  \n",
       "1  2b416f1d7e89ad3b  \n",
       "2  ff71a556d86c4b8f  \n",
       "3  cf1527a0b4173e8f  \n",
       "4  cbc62c2b1cb7deb9  \n",
       "5  1488e4c1cc8f1c55  \n",
       "6  597d295ddce706f7  \n",
       "7  9d3961d2ea1944fc  \n",
       "8  80e715671282e957  \n",
       "9  3fa05a459ddaa70d  \n",
       "\n",
       "[10 rows x 27 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_X_tr.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_X_op = pd.read_csv('D:/transaction_risk_competition/operation_train_new.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>UID</th>\n",
       "      <th>day</th>\n",
       "      <th>mode</th>\n",
       "      <th>success</th>\n",
       "      <th>time</th>\n",
       "      <th>os</th>\n",
       "      <th>version</th>\n",
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       "      <th>device2</th>\n",
       "      <th>device_code1</th>\n",
       "      <th>device_code2</th>\n",
       "      <th>device_code3</th>\n",
       "      <th>mac1</th>\n",
       "      <th>mac2</th>\n",
       "      <th>ip1</th>\n",
       "      <th>ip2</th>\n",
       "      <th>wifi</th>\n",
       "      <th>geo_code</th>\n",
       "      <th>ip1_sub</th>\n",
       "      <th>ip2_sub</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10035</td>\n",
       "      <td>30</td>\n",
       "      <td>c8741ce15ceac2a4</td>\n",
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       "      <td>102</td>\n",
       "      <td>7.0.9</td>\n",
       "      <td>49dd36968dbfadda</td>\n",
       "      <td>OPPO R11</td>\n",
       "      <td>ecb58082e0e9b8e2</td>\n",
       "      <td>00fa2e4ba95605ef</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a8dc52f65085212e</td>\n",
       "      <td>55dd8936655c86f6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>wskx</td>\n",
       "      <td>e58e48fb9215116e</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>16264</td>\n",
       "      <td>16</td>\n",
       "      <td>20a91b45ef8f8221</td>\n",
       "      <td>1.0</td>\n",
       "      <td>08:36:00</td>\n",
       "      <td>200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>fc7fc47d6c93f554</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3502c553ea2ac187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>13162</td>\n",
       "      <td>8</td>\n",
       "      <td>b668e42707ee9c7b</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18:09:57</td>\n",
       "      <td>102</td>\n",
       "      <td>7.0.5</td>\n",
       "      <td>630a1adff2a87007</td>\n",
       "      <td>MI MAX 2</td>\n",
       "      <td>1da225cb679a37eb</td>\n",
       "      <td>f18538156b8f9b57</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a8dc52f65085212e</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2147d925e7a8ba3c</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3591678eca3f7a23</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>21392</td>\n",
       "      <td>23</td>\n",
       "      <td>c8741ce15ceac2a4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>23:53:49</td>\n",
       "      <td>102</td>\n",
       "      <td>7.0.9</td>\n",
       "      <td>630a1adff2a87007</td>\n",
       "      <td>MI 5X</td>\n",
       "      <td>d0c285513b785609</td>\n",
       "      <td>a7e79e3c2c85c8c7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>04a2d6c090518faa</td>\n",
       "      <td>c52efc665f0af581</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4ff1553b1c96360e</td>\n",
       "      <td>wm4v</td>\n",
       "      <td>fdb5e20f6a6f2cd7</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>18599</td>\n",
       "      <td>26</td>\n",
       "      <td>acfaded7e04e7ba0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>11:11:15</td>\n",
       "      <td>102</td>\n",
       "      <td>7.0.0</td>\n",
       "      <td>8399be6b80847240</td>\n",
       "      <td>NaN</td>\n",
       "      <td>27efd832595503f6</td>\n",
       "      <td>b6457e2264266257</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1ab9dc3eae102aa6</td>\n",
       "      <td>0fe293bea342665a</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f5009e2c6c13c80c</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>20499</td>\n",
       "      <td>27</td>\n",
       "      <td>c8741ce15ceac2a4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>16:44:31</td>\n",
       "      <td>102</td>\n",
       "      <td>7.0.9</td>\n",
       "      <td>a92470e4f878a3f4</td>\n",
       "      <td>M6 NOTE</td>\n",
       "      <td>2bd7dd548de5c1eb</td>\n",
       "      <td>a3f306f70f99d3c5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a8dc52f65085212e</td>\n",
       "      <td>907bb247d8ab8fdd</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ws90</td>\n",
       "      <td>46649b2cd10a7d41</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>21634</td>\n",
       "      <td>27</td>\n",
       "      <td>c8741ce15ceac2a4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>21:02:12</td>\n",
       "      <td>102</td>\n",
       "      <td>7.0.9</td>\n",
       "      <td>dcc26c88f36170cc</td>\n",
       "      <td>SM-G955F</td>\n",
       "      <td>c50faf7eba139d67</td>\n",
       "      <td>483ddc3a31666b8f</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>b910ea1cd2e10a1d</td>\n",
       "      <td>211d0e54f3da2e8d</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6ec718bbccbaedd2</td>\n",
       "      <td>ws45</td>\n",
       "      <td>d7833f8214e8019f</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>11305</td>\n",
       "      <td>8</td>\n",
       "      <td>c8741ce15ceac2a4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>18:59:56</td>\n",
       "      <td>102</td>\n",
       "      <td>7.0.5</td>\n",
       "      <td>a92470e4f878a3f4</td>\n",
       "      <td>M3 MAX</td>\n",
       "      <td>39c97da95ebca34e</td>\n",
       "      <td>476e25c0b0bcfa97</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a8dc52f65085212e</td>\n",
       "      <td>1c682213d73d8f41</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ws2x</td>\n",
       "      <td>5ec2ddaaa2c6a044</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>15270</td>\n",
       "      <td>19</td>\n",
       "      <td>479617cd802ed152</td>\n",
       "      <td>1.0</td>\n",
       "      <td>09:12:26</td>\n",
       "      <td>200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>fa3ae43e9f767109</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>f9c9ec38dd0f9149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10655</td>\n",
       "      <td>16</td>\n",
       "      <td>c8741ce15ceac2a4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>15:25:32</td>\n",
       "      <td>102</td>\n",
       "      <td>7.0.5</td>\n",
       "      <td>8f970961c66d9ec6</td>\n",
       "      <td>ZTE V0840</td>\n",
       "      <td>9778c2c441240765</td>\n",
       "      <td>e7a501e84cf8c9b9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a8dc52f65085212e</td>\n",
       "      <td>9549680e109c5d8c</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ws82</td>\n",
       "      <td>cadff7d686628ff8</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     UID  day              mode  success      time   os version  \\\n",
       "0  10035   30  c8741ce15ceac2a4      1.0  17:51:50  102   7.0.9   \n",
       "1  16264   16  20a91b45ef8f8221      1.0  08:36:00  200     NaN   \n",
       "2  13162    8  b668e42707ee9c7b      0.0  18:09:57  102   7.0.5   \n",
       "3  21392   23  c8741ce15ceac2a4      1.0  23:53:49  102   7.0.9   \n",
       "4  18599   26  acfaded7e04e7ba0      1.0  11:11:15  102   7.0.0   \n",
       "5  20499   27  c8741ce15ceac2a4      1.0  16:44:31  102   7.0.9   \n",
       "6  21634   27  c8741ce15ceac2a4      1.0  21:02:12  102   7.0.9   \n",
       "7  11305    8  c8741ce15ceac2a4      1.0  18:59:56  102   7.0.5   \n",
       "8  15270   19  479617cd802ed152      1.0  09:12:26  200     NaN   \n",
       "9  10655   16  c8741ce15ceac2a4      1.0  15:25:32  102   7.0.5   \n",
       "\n",
       "            device1    device2      device_code1      device_code2  \\\n",
       "0  49dd36968dbfadda   OPPO R11  ecb58082e0e9b8e2  00fa2e4ba95605ef   \n",
       "1               NaN        NaN               NaN               NaN   \n",
       "2  630a1adff2a87007   MI MAX 2  1da225cb679a37eb  f18538156b8f9b57   \n",
       "3  630a1adff2a87007      MI 5X  d0c285513b785609  a7e79e3c2c85c8c7   \n",
       "4  8399be6b80847240        NaN  27efd832595503f6  b6457e2264266257   \n",
       "5  a92470e4f878a3f4    M6 NOTE  2bd7dd548de5c1eb  a3f306f70f99d3c5   \n",
       "6  dcc26c88f36170cc   SM-G955F  c50faf7eba139d67  483ddc3a31666b8f   \n",
       "7  a92470e4f878a3f4     M3 MAX  39c97da95ebca34e  476e25c0b0bcfa97   \n",
       "8               NaN        NaN               NaN               NaN   \n",
       "9  8f970961c66d9ec6  ZTE V0840  9778c2c441240765  e7a501e84cf8c9b9   \n",
       "\n",
       "  device_code3              mac1              mac2               ip1  \\\n",
       "0          NaN               NaN  a8dc52f65085212e  55dd8936655c86f6   \n",
       "1          NaN               NaN               NaN               NaN   \n",
       "2          NaN  a8dc52f65085212e               NaN  2147d925e7a8ba3c   \n",
       "3          NaN               NaN  04a2d6c090518faa  c52efc665f0af581   \n",
       "4          NaN               NaN  1ab9dc3eae102aa6  0fe293bea342665a   \n",
       "5          NaN               NaN  a8dc52f65085212e  907bb247d8ab8fdd   \n",
       "6          NaN               NaN  b910ea1cd2e10a1d  211d0e54f3da2e8d   \n",
       "7          NaN               NaN  a8dc52f65085212e  1c682213d73d8f41   \n",
       "8          NaN               NaN               NaN               NaN   \n",
       "9          NaN               NaN  a8dc52f65085212e  9549680e109c5d8c   \n",
       "\n",
       "                ip2              wifi geo_code           ip1_sub  \\\n",
       "0               NaN               NaN     wskx  e58e48fb9215116e   \n",
       "1  fc7fc47d6c93f554               NaN      NaN               NaN   \n",
       "2               NaN               NaN      NaN  3591678eca3f7a23   \n",
       "3               NaN  4ff1553b1c96360e     wm4v  fdb5e20f6a6f2cd7   \n",
       "4               NaN               NaN      NaN  f5009e2c6c13c80c   \n",
       "5               NaN               NaN     ws90  46649b2cd10a7d41   \n",
       "6               NaN  6ec718bbccbaedd2     ws45  d7833f8214e8019f   \n",
       "7               NaN               NaN     ws2x  5ec2ddaaa2c6a044   \n",
       "8  fa3ae43e9f767109               NaN      NaN               NaN   \n",
       "9               NaN               NaN     ws82  cadff7d686628ff8   \n",
       "\n",
       "            ip2_sub  \n",
       "0               NaN  \n",
       "1  3502c553ea2ac187  \n",
       "2               NaN  \n",
       "3               NaN  \n",
       "4               NaN  \n",
       "5               NaN  \n",
       "6               NaN  \n",
       "7               NaN  \n",
       "8  f9c9ec38dd0f9149  \n",
       "9               NaN  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_X_op.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['UID',\n",
       " 'channel',\n",
       " 'day',\n",
       " 'time',\n",
       " 'trans_amt',\n",
       " 'amt_src1',\n",
       " 'merchant',\n",
       " 'code1',\n",
       " 'code2',\n",
       " 'trans_type1',\n",
       " 'acc_id1',\n",
       " 'device_code1',\n",
       " 'device_code2',\n",
       " 'device_code3',\n",
       " 'device1',\n",
       " 'device2',\n",
       " 'mac1',\n",
       " 'ip1',\n",
       " 'bal',\n",
       " 'amt_src2',\n",
       " 'acc_id2',\n",
       " 'acc_id3',\n",
       " 'geo_code',\n",
       " 'trans_type2',\n",
       " 'market_code',\n",
       " 'market_type',\n",
       " 'ip1_sub']"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(train_X_tr.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_X_tr=train_X_tr[['UID','day','time','trans_amt','bal','acc_id1','acc_id2','acc_id3','amt_src1','amt_src2','trans_type2','trans_type1','market_code','market_type','merchant','code1','code2','channel','device_code1','device_code2','device_code3','device1','device2','mac1','ip1','ip1_sub','geo_code']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>UID</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>trans_amt</th>\n",
       "      <th>bal</th>\n",
       "      <th>acc_id1</th>\n",
       "      <th>acc_id2</th>\n",
       "      <th>acc_id3</th>\n",
       "      <th>amt_src1</th>\n",
       "      <th>amt_src2</th>\n",
       "      <th>trans_type2</th>\n",
       "      <th>trans_type1</th>\n",
       "      <th>market_code</th>\n",
       "      <th>market_type</th>\n",
       "      <th>merchant</th>\n",
       "      <th>code1</th>\n",
       "      <th>code2</th>\n",
       "      <th>channel</th>\n",
       "      <th>device_code1</th>\n",
       "      <th>device_code2</th>\n",
       "      <th>device_code3</th>\n",
       "      <th>device1</th>\n",
       "      <th>device2</th>\n",
       "      <th>mac1</th>\n",
       "      <th>ip1</th>\n",
       "      <th>ip1_sub</th>\n",
       "      <th>geo_code</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19092</td>\n",
       "      <td>30</td>\n",
       "      <td>11:48:47</td>\n",
       "      <td>1459</td>\n",
       "      <td>1007</td>\n",
       "      <td>544dfdeedad0ae67</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>acdbdb842ac20f1e</td>\n",
       "      <td>9fefed0a981dcb7a</td>\n",
       "      <td>102.0</td>\n",
       "      <td>26bcf43a19df14c8</td>\n",
       "      <td>2ecf94369847c748</td>\n",
       "      <td>1.0</td>\n",
       "      <td>abc6bc660561e0eb</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>102</td>\n",
       "      <td>ffda8eaa413171cb</td>\n",
       "      <td>b36097d8a79e5b43</td>\n",
       "      <td>NaN</td>\n",
       "      <td>d2cf44cec09806cc</td>\n",
       "      <td>VIVO X9L</td>\n",
       "      <td>7aaec0f23bfa60ea</td>\n",
       "      <td>a664530c1fb20abe</td>\n",
       "      <td>45f4ca1f4e9b9cb7</td>\n",
       "      <td>wsbq</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>13465</td>\n",
       "      <td>23</td>\n",
       "      <td>16:58:03</td>\n",
       "      <td>725</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4d7831c6f695ab19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>105.0</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7a87b1aa20972d48</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>140</td>\n",
       "      <td>0e305dafdd3af261</td>\n",
       "      <td>365ec16ad4006c4f</td>\n",
       "      <td>NaN</td>\n",
       "      <td>09baf2f39bc3dc86</td>\n",
       "      <td>NEM-AL10</td>\n",
       "      <td>6f675a9b2124d2f8</td>\n",
       "      <td>52abe1e300a8aa10</td>\n",
       "      <td>2b416f1d7e89ad3b</td>\n",
       "      <td>wte7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>13713</td>\n",
       "      <td>22</td>\n",
       "      <td>09:56:39</td>\n",
       "      <td>127</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c5fc631370cabc0d</td>\n",
       "      <td>NaN</td>\n",
       "      <td>105.0</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>cfd035fc7e0a53b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>140</td>\n",
       "      <td>429d5656ba8f3d01</td>\n",
       "      <td>760cfbfc0c2e3b49</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a92470e4f878a3f4</td>\n",
       "      <td>M3X</td>\n",
       "      <td>99a5f1ff7f3e54f0</td>\n",
       "      <td>e4c132d02ff6c095</td>\n",
       "      <td>ff71a556d86c4b8f</td>\n",
       "      <td>ws7n</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>22703</td>\n",
       "      <td>1</td>\n",
       "      <td>18:11:45</td>\n",
       "      <td>99317</td>\n",
       "      <td>100</td>\n",
       "      <td>516e596377b2019c</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a571c7fda8b7df37</td>\n",
       "      <td>fbf6bf3c8927414c</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c71c876b8979028e</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>140</td>\n",
       "      <td>609954adce541306</td>\n",
       "      <td>31989e264685a18c</td>\n",
       "      <td>NaN</td>\n",
       "      <td>09baf2f39bc3dc86</td>\n",
       "      <td>KNT-UL10</td>\n",
       "      <td>a8dc52f65085212e</td>\n",
       "      <td>e1c78a56cc9dfc8b</td>\n",
       "      <td>cf1527a0b4173e8f</td>\n",
       "      <td>wqj6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>17816</td>\n",
       "      <td>22</td>\n",
       "      <td>13:04:02</td>\n",
       "      <td>3361</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c5fc631370cabc0d</td>\n",
       "      <td>NaN</td>\n",
       "      <td>105.0</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6628f5ca013e3582</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>140</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2f61e8f52151bd8b</td>\n",
       "      <td>aca4977fbe8741e1</td>\n",
       "      <td>IPHONE 5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>abb6b4b8f15be6d6</td>\n",
       "      <td>cbc62c2b1cb7deb9</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>12037</td>\n",
       "      <td>8</td>\n",
       "      <td>01:09:29</td>\n",
       "      <td>5536</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>d7de70fc65292e41</td>\n",
       "      <td>079946f395cc0cf1</td>\n",
       "      <td>102.0</td>\n",
       "      <td>6d55c54c8b1056fb</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3f6d3d0f42519ea4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>102</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6113d5f9c8a65ea8</td>\n",
       "      <td>aca4977fbe8741e1</td>\n",
       "      <td>IPHONE 5S</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35d6ccb3b4ff776a</td>\n",
       "      <td>1488e4c1cc8f1c55</td>\n",
       "      <td>wwhu</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     UID  day      time  trans_amt   bal           acc_id1 acc_id2 acc_id3  \\\n",
       "0  19092   30  11:48:47       1459  1007  544dfdeedad0ae67     NaN     NaN   \n",
       "1  13465   23  16:58:03        725   100               NaN     NaN     NaN   \n",
       "2  13713   22  09:56:39        127   100               NaN     NaN     NaN   \n",
       "3  22703    1  18:11:45      99317   100  516e596377b2019c     NaN     NaN   \n",
       "4  17816   22  13:04:02       3361   100               NaN     NaN     NaN   \n",
       "5  12037    8  01:09:29       5536   100               NaN     NaN     NaN   \n",
       "\n",
       "           amt_src1          amt_src2  trans_type2       trans_type1  \\\n",
       "0  acdbdb842ac20f1e  9fefed0a981dcb7a        102.0  26bcf43a19df14c8   \n",
       "1  4d7831c6f695ab19               NaN        105.0  c2f2023d279665b2   \n",
       "2  c5fc631370cabc0d               NaN        105.0  c2f2023d279665b2   \n",
       "3  a571c7fda8b7df37  fbf6bf3c8927414c          NaN  c2f2023d279665b2   \n",
       "4  c5fc631370cabc0d               NaN        105.0  c2f2023d279665b2   \n",
       "5  d7de70fc65292e41  079946f395cc0cf1        102.0  6d55c54c8b1056fb   \n",
       "\n",
       "        market_code  market_type          merchant code1 code2  channel  \\\n",
       "0  2ecf94369847c748          1.0  abc6bc660561e0eb   NaN   NaN      102   \n",
       "1               NaN          NaN  7a87b1aa20972d48   NaN   NaN      140   \n",
       "2               NaN          NaN  cfd035fc7e0a53b2   NaN   NaN      140   \n",
       "3               NaN          NaN  c71c876b8979028e   NaN   NaN      140   \n",
       "4               NaN          NaN  6628f5ca013e3582   NaN   NaN      140   \n",
       "5               NaN          NaN  3f6d3d0f42519ea4   NaN   NaN      102   \n",
       "\n",
       "       device_code1      device_code2      device_code3           device1  \\\n",
       "0  ffda8eaa413171cb  b36097d8a79e5b43               NaN  d2cf44cec09806cc   \n",
       "1  0e305dafdd3af261  365ec16ad4006c4f               NaN  09baf2f39bc3dc86   \n",
       "2  429d5656ba8f3d01  760cfbfc0c2e3b49               NaN  a92470e4f878a3f4   \n",
       "3  609954adce541306  31989e264685a18c               NaN  09baf2f39bc3dc86   \n",
       "4               NaN               NaN  2f61e8f52151bd8b  aca4977fbe8741e1   \n",
       "5               NaN               NaN  6113d5f9c8a65ea8  aca4977fbe8741e1   \n",
       "\n",
       "     device2              mac1               ip1           ip1_sub geo_code  \n",
       "0   VIVO X9L  7aaec0f23bfa60ea  a664530c1fb20abe  45f4ca1f4e9b9cb7     wsbq  \n",
       "1   NEM-AL10  6f675a9b2124d2f8  52abe1e300a8aa10  2b416f1d7e89ad3b     wte7  \n",
       "2        M3X  99a5f1ff7f3e54f0  e4c132d02ff6c095  ff71a556d86c4b8f     ws7n  \n",
       "3   KNT-UL10  a8dc52f65085212e  e1c78a56cc9dfc8b  cf1527a0b4173e8f     wqj6  \n",
       "4   IPHONE 5               NaN  abb6b4b8f15be6d6  cbc62c2b1cb7deb9      NaN  \n",
       "5  IPHONE 5S               NaN  35d6ccb3b4ff776a  1488e4c1cc8f1c55     wwhu  "
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_X_tr.head(6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>UID</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>trans_amt</th>\n",
       "      <th>bal</th>\n",
       "      <th>acc_id1</th>\n",
       "      <th>acc_id2</th>\n",
       "      <th>acc_id3</th>\n",
       "      <th>amt_src1</th>\n",
       "      <th>amt_src2</th>\n",
       "      <th>trans_type2</th>\n",
       "      <th>trans_type1</th>\n",
       "      <th>market_code</th>\n",
       "      <th>market_type</th>\n",
       "      <th>merchant</th>\n",
       "      <th>code1</th>\n",
       "      <th>code2</th>\n",
       "      <th>channel</th>\n",
       "      <th>device_code1</th>\n",
       "      <th>device_code2</th>\n",
       "      <th>device_code3</th>\n",
       "      <th>device1</th>\n",
       "      <th>device2</th>\n",
       "      <th>mac1</th>\n",
       "      <th>ip1</th>\n",
       "      <th>ip1_sub</th>\n",
       "      <th>geo_code</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19092</td>\n",
       "      <td>30</td>\n",
       "      <td>11:48:47</td>\n",
       "      <td>1459</td>\n",
       "      <td>1007</td>\n",
       "      <td>544dfdeedad0ae67</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>acdbdb842ac20f1e</td>\n",
       "      <td>9fefed0a981dcb7a</td>\n",
       "      <td>102.0</td>\n",
       "      <td>26bcf43a19df14c8</td>\n",
       "      <td>2ecf94369847c748</td>\n",
       "      <td>1.0</td>\n",
       "      <td>abc6bc660561e0eb</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>102</td>\n",
       "      <td>ffda8eaa413171cb</td>\n",
       "      <td>b36097d8a79e5b43</td>\n",
       "      <td>NaN</td>\n",
       "      <td>d2cf44cec09806cc</td>\n",
       "      <td>VIVO X9L</td>\n",
       "      <td>7aaec0f23bfa60ea</td>\n",
       "      <td>a664530c1fb20abe</td>\n",
       "      <td>45f4ca1f4e9b9cb7</td>\n",
       "      <td>wsbq</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     UID  day      time  trans_amt   bal           acc_id1 acc_id2 acc_id3  \\\n",
       "0  19092   30  11:48:47       1459  1007  544dfdeedad0ae67     NaN     NaN   \n",
       "\n",
       "           amt_src1          amt_src2  trans_type2       trans_type1  \\\n",
       "0  acdbdb842ac20f1e  9fefed0a981dcb7a        102.0  26bcf43a19df14c8   \n",
       "\n",
       "        market_code  market_type          merchant code1 code2  channel  \\\n",
       "0  2ecf94369847c748          1.0  abc6bc660561e0eb   NaN   NaN      102   \n",
       "\n",
       "       device_code1      device_code2 device_code3           device1  \\\n",
       "0  ffda8eaa413171cb  b36097d8a79e5b43          NaN  d2cf44cec09806cc   \n",
       "\n",
       "    device2              mac1               ip1           ip1_sub geo_code  \n",
       "0  VIVO X9L  7aaec0f23bfa60ea  a664530c1fb20abe  45f4ca1f4e9b9cb7     wsbq  "
      ]
     },
     "execution_count": 179,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#显示所有列\n",
    "pd.set_option('display.max_columns', None)\n",
    "#显示所有行\n",
    "#pd.set_option('display.max_rows', None)\n",
    "#设置value的显示长度为100，默认为50\n",
    "pd.set_option('max_colwidth',100)\n",
    "\n",
    "train_X_tr.head(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "wt7j    7312\n",
       "wqq2    2518\n",
       "wxkz    1994\n",
       "ws06    1889\n",
       "wxsb    1769\n",
       "wmgu    1708\n",
       "wtfh    1559\n",
       "webw    1506\n",
       "wkp7    1469\n",
       "ws3j    1468\n",
       "ws0e    1379\n",
       "wt5c    1363\n",
       "w7w3    1303\n",
       "ww9w    1209\n",
       "wsbq    1130\n",
       "ww5j    1129\n",
       "ws2r    1101\n",
       "wmd6    1083\n",
       "wmr8    1016\n",
       "wkzc     964\n",
       "wwj1     957\n",
       "weby     921\n",
       "wmuh     915\n",
       "wt59     852\n",
       "wm65     825\n",
       "wtsk     791\n",
       "ws07     789\n",
       "wme1     788\n",
       "wqnr     781\n",
       "wth5     752\n",
       "ww8y     740\n",
       "ww4g     736\n",
       "wxy3     726\n",
       "y8th     715\n",
       "ws4u     703\n",
       "ws05     702\n",
       "wm4u     687\n",
       "wtq3     685\n",
       "wrhr     677\n",
       "vb79     653\n",
       "wmd0     648\n",
       "wt58     646\n",
       "wt5f     635\n",
       "wt5t     628\n",
       "wss8     620\n",
       "ww9x     615\n",
       "wqj7     607\n",
       "ws7n     580\n",
       "wmu5     576\n",
       "wsb1     572\n",
       "ws3n     570\n",
       "wxrt     565\n",
       "ws1x     565\n",
       "ws2y     558\n",
       "wm4x     556\n",
       "wwc2     552\n",
       "wx85     552\n",
       "wmeb     550\n",
       "wtg1     538\n",
       "wxs8     534\n",
       "wth4     520\n",
       "y8tp     516\n",
       "wxss     516\n",
       "ws3b     510\n",
       "wts4     509\n",
       "wkxw     506\n",
       "wxrv     506\n",
       "wm57     484\n",
       "ws4t     474\n",
       "ww8z     472\n",
       "wxy2     468\n",
       "wtem     458\n",
       "wt02     455\n",
       "ws2n     443\n",
       "tzy4     443\n",
       "wx4g     431\n",
       "wkj1     425\n",
       "wt7m     423\n",
       "wme9     422\n",
       "ws4y     420\n",
       "wsbx     416\n",
       "wmgg     416\n",
       "ws10     412\n",
       "wmuk     408\n",
       "ws17     407\n",
       "wwfy     406\n",
       "wsgv     402\n",
       "wtw3     402\n",
       "wskm     399\n",
       "ww0v     399\n",
       "wme6     397\n",
       "wmr2     396\n",
       "wkfr     395\n",
       "wkpk     391\n",
       "wtm1     390\n",
       "wtf5     389\n",
       "wm4r     388\n",
       "wqjy     386\n",
       "wm3y     386\n",
       "wkrn     384\n",
       "wqj6     383\n",
       "wq3v     382\n",
       "ybbc     382\n",
       "wxsc     377\n",
       "wx4e     375\n",
       "wq5n     372\n",
       "wqtm     371\n",
       "wkxb     367\n",
       "wwhe     366\n",
       "wkz6     364\n",
       "wwhc     363\n",
       "ws2v     362\n",
       "wxuf     355\n",
       "wtf7     354\n",
       "wmev     348\n",
       "ws0d     347\n",
       "wkr8     343\n",
       "wt5b     334\n",
       "wk8v     332\n",
       "wm6n     329\n",
       "wm4y     328\n",
       "wt3m     325\n",
       "wtg7     316\n",
       "wrnp     316\n",
       "wm7s     314\n",
       "wxug     314\n",
       "wm7r     313\n",
       "ws1t     308\n",
       "wkxx     305\n",
       "wm3g     304\n",
       "wkez     302\n",
       "ww8x     302\n",
       "wm4w     300\n",
       "wxze     298\n",
       "wqhf     298\n",
       "wmpn     297\n",
       "ws0q     296\n",
       "wsb0     294\n",
       "wsby     293\n",
       "wrjr     293\n",
       "wm69     288\n",
       "wkpg     287\n",
       "wm3f     286\n",
       "wxy0     286\n",
       "wqpt     286\n",
       "whxh     284\n",
       "ws0s     283\n",
       "ws3k     282\n",
       "wkpu     281\n",
       "wkzj     279\n",
       "wtcx     279\n",
       "ws76     278\n",
       "wt09     277\n",
       "ww28     275\n",
       "ww56     272\n",
       "ww9t     271\n",
       "wxy6     270\n",
       "wsbz     270\n",
       "wxf9     270\n",
       "wm47     268\n",
       "wt52     268\n",
       "wtjq     265\n",
       "wrr2     264\n",
       "wm6s     262\n",
       "wxxc     262\n",
       "wm3t     260\n",
       "wkqy     259\n",
       "ws7g     258\n",
       "wk8r     257\n",
       "ww5h     256\n",
       "wtsq     256\n",
       "wssu     255\n",
       "yb3s     254\n",
       "wset     254\n",
       "wtub     251\n",
       "wsvz     251\n",
       "wm3b     251\n",
       "wtm7     248\n",
       "wtmk     248\n",
       "y9n2     244\n",
       "wqq3     244\n",
       "wkhe     244\n",
       "tzy3     241\n",
       "wt53     240\n",
       "ws14     239\n",
       "ws0g     238\n",
       "wt4z     234\n",
       "wtmh     234\n",
       "wt08     231\n",
       "wkzs     230\n",
       "wm4t     230\n",
       "wmpm     230\n",
       "wmdd     226\n",
       "ws08     223\n",
       "wtk1     221\n",
       "wtq6     221\n",
       "wwc3     220\n",
       "wsbj     218\n",
       "wtvk     218\n",
       "wtvm     213\n",
       "ws0f     212\n",
       "wtgp     212\n",
       "webx     211\n",
       "ws82     210\n",
       "ws45     209\n",
       "ws7e     209\n",
       "wt47     207\n",
       "ws02     206\n",
       "ww5k     205\n",
       "ws4v     204\n",
       "wmpj     204\n",
       "wmd7     204\n",
       "wtfe     203\n",
       "wm2j     203\n",
       "ws34     203\n",
       "wkzm     202\n",
       "ws0u     200\n",
       "wm48     199\n",
       "wtek     199\n",
       "wwcg     197\n",
       "wkjj     195\n",
       "wm3z     195\n",
       "ws1w     194\n",
       "wth1     194\n",
       "wwe0     193\n",
       "wtte     193\n",
       "wssh     193\n",
       "ww8p     193\n",
       "wtw4     193\n",
       "wkzh     190\n",
       "wwh5     189\n",
       "wq6p     188\n",
       "wkz7     188\n",
       "ws61     186\n",
       "ws09     186\n",
       "y8wp     185\n",
       "wmue     185\n",
       "wk8t     185\n",
       "wwgq     185\n",
       "yb51     184\n",
       "wxrd     184\n",
       "wt12     184\n",
       "ww9z     184\n",
       "wmpz     183\n",
       "wt4f     183\n",
       "wskp     183\n",
       "wtt7     180\n",
       "y8x1     180\n",
       "wt5s     178\n",
       "wtjt     178\n",
       "wsbf     178\n",
       "wtgf     177\n",
       "wmum     177\n",
       "wqju     177\n",
       "wmd1     176\n",
       "wm64     176\n",
       "wsgg     176\n",
       "ws11     176\n",
       "ws3c     171\n",
       "wj2b     170\n",
       "wx4d     168\n",
       "ws03     168\n",
       "y8ny     167\n",
       "ws13     167\n",
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       "Name: geo_code, dtype: int64"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#统计各列字段的不完整性\n",
    "#train_X_tr['acc_id1'].value_counts()#只计算非空值\n",
    "#train_X_tr['acc_id1'].apply(lambda x :x/df['Prices'].sum())\n",
    "#train_X_tr['acc_id1'].count()\n",
    "\n",
    "# len_count=len(train_X_tr['UID'])\n",
    "# for col in ['UID','day','time','trans_amt','bal','acc_id1','acc_id2','acc_id3','amt_src1','amt_src2','trans_type2','trans_type1','market_code','market_type','merchant','code1','code2','channel','device_code1','device_code2','device_code3','device1','device2','mac1','ip1','ip1_sub','geo_code']:\n",
    "#     print('{0}'.format(col),  '%.2f' %(train_X_tr[col].isnull().sum()/len_count))\n",
    "\n",
    "#需要因子化的列，\n",
    "#train_X_tr['amt_src1'].value_counts()\n",
    "#显示所有行\n",
    "pd.set_option('display.max_rows', None)\n",
    "train_X_tr['geo_code'].value_counts()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>UID</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>trans_amt</th>\n",
       "      <th>bal</th>\n",
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       "      <th>code1</th>\n",
       "      <th>code2</th>\n",
       "      <th>channel</th>\n",
       "      <th>device_code1</th>\n",
       "      <th>device_code2</th>\n",
       "      <th>device_code3</th>\n",
       "      <th>device1</th>\n",
       "      <th>device2</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19092</td>\n",
       "      <td>30</td>\n",
       "      <td>11:48:47</td>\n",
       "      <td>1459</td>\n",
       "      <td>1007</td>\n",
       "      <td>544dfdeedad0ae67</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>acdbdb842ac20f1e</td>\n",
       "      <td>9fefed0a981dcb7a</td>\n",
       "      <td>102.0</td>\n",
       "      <td>26bcf43a19df14c8</td>\n",
       "      <td>2ecf94369847c748</td>\n",
       "      <td>1.0</td>\n",
       "      <td>abc6bc660561e0eb</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>102</td>\n",
       "      <td>ffda8eaa413171cb</td>\n",
       "      <td>b36097d8a79e5b43</td>\n",
       "      <td>NaN</td>\n",
       "      <td>d2cf44cec09806cc</td>\n",
       "      <td>VIVO X9L</td>\n",
       "      <td>7aaec0f23bfa60ea</td>\n",
       "      <td>a664530c1fb20abe</td>\n",
       "      <td>45f4ca1f4e9b9cb7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>13465</td>\n",
       "      <td>23</td>\n",
       "      <td>16:58:03</td>\n",
       "      <td>725</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4d7831c6f695ab19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>105.0</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7a87b1aa20972d48</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>140</td>\n",
       "      <td>0e305dafdd3af261</td>\n",
       "      <td>365ec16ad4006c4f</td>\n",
       "      <td>NaN</td>\n",
       "      <td>09baf2f39bc3dc86</td>\n",
       "      <td>NEM-AL10</td>\n",
       "      <td>6f675a9b2124d2f8</td>\n",
       "      <td>52abe1e300a8aa10</td>\n",
       "      <td>2b416f1d7e89ad3b</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>13713</td>\n",
       "      <td>22</td>\n",
       "      <td>09:56:39</td>\n",
       "      <td>127</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c5fc631370cabc0d</td>\n",
       "      <td>NaN</td>\n",
       "      <td>105.0</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>cfd035fc7e0a53b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>140</td>\n",
       "      <td>429d5656ba8f3d01</td>\n",
       "      <td>760cfbfc0c2e3b49</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a92470e4f878a3f4</td>\n",
       "      <td>M3X</td>\n",
       "      <td>99a5f1ff7f3e54f0</td>\n",
       "      <td>e4c132d02ff6c095</td>\n",
       "      <td>ff71a556d86c4b8f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>22703</td>\n",
       "      <td>1</td>\n",
       "      <td>18:11:45</td>\n",
       "      <td>99317</td>\n",
       "      <td>100</td>\n",
       "      <td>516e596377b2019c</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a571c7fda8b7df37</td>\n",
       "      <td>fbf6bf3c8927414c</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c71c876b8979028e</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>140</td>\n",
       "      <td>609954adce541306</td>\n",
       "      <td>31989e264685a18c</td>\n",
       "      <td>NaN</td>\n",
       "      <td>09baf2f39bc3dc86</td>\n",
       "      <td>KNT-UL10</td>\n",
       "      <td>a8dc52f65085212e</td>\n",
       "      <td>e1c78a56cc9dfc8b</td>\n",
       "      <td>cf1527a0b4173e8f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>17816</td>\n",
       "      <td>22</td>\n",
       "      <td>13:04:02</td>\n",
       "      <td>3361</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c5fc631370cabc0d</td>\n",
       "      <td>NaN</td>\n",
       "      <td>105.0</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6628f5ca013e3582</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>140</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2f61e8f52151bd8b</td>\n",
       "      <td>aca4977fbe8741e1</td>\n",
       "      <td>IPHONE 5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>abb6b4b8f15be6d6</td>\n",
       "      <td>cbc62c2b1cb7deb9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     UID  day      time  trans_amt   bal           acc_id1 acc_id2 acc_id3  \\\n",
       "0  19092   30  11:48:47       1459  1007  544dfdeedad0ae67     NaN     NaN   \n",
       "1  13465   23  16:58:03        725   100               NaN     NaN     NaN   \n",
       "2  13713   22  09:56:39        127   100               NaN     NaN     NaN   \n",
       "3  22703    1  18:11:45      99317   100  516e596377b2019c     NaN     NaN   \n",
       "4  17816   22  13:04:02       3361   100               NaN     NaN     NaN   \n",
       "\n",
       "           amt_src1          amt_src2  trans_type2       trans_type1  \\\n",
       "0  acdbdb842ac20f1e  9fefed0a981dcb7a        102.0  26bcf43a19df14c8   \n",
       "1  4d7831c6f695ab19               NaN        105.0  c2f2023d279665b2   \n",
       "2  c5fc631370cabc0d               NaN        105.0  c2f2023d279665b2   \n",
       "3  a571c7fda8b7df37  fbf6bf3c8927414c          NaN  c2f2023d279665b2   \n",
       "4  c5fc631370cabc0d               NaN        105.0  c2f2023d279665b2   \n",
       "\n",
       "        market_code  market_type          merchant code1 code2  channel  \\\n",
       "0  2ecf94369847c748          1.0  abc6bc660561e0eb   NaN   NaN      102   \n",
       "1               NaN          NaN  7a87b1aa20972d48   NaN   NaN      140   \n",
       "2               NaN          NaN  cfd035fc7e0a53b2   NaN   NaN      140   \n",
       "3               NaN          NaN  c71c876b8979028e   NaN   NaN      140   \n",
       "4               NaN          NaN  6628f5ca013e3582   NaN   NaN      140   \n",
       "\n",
       "       device_code1      device_code2      device_code3           device1  \\\n",
       "0  ffda8eaa413171cb  b36097d8a79e5b43               NaN  d2cf44cec09806cc   \n",
       "1  0e305dafdd3af261  365ec16ad4006c4f               NaN  09baf2f39bc3dc86   \n",
       "2  429d5656ba8f3d01  760cfbfc0c2e3b49               NaN  a92470e4f878a3f4   \n",
       "3  609954adce541306  31989e264685a18c               NaN  09baf2f39bc3dc86   \n",
       "4               NaN               NaN  2f61e8f52151bd8b  aca4977fbe8741e1   \n",
       "\n",
       "    device2              mac1               ip1           ip1_sub  \n",
       "0  VIVO X9L  7aaec0f23bfa60ea  a664530c1fb20abe  45f4ca1f4e9b9cb7  \n",
       "1  NEM-AL10  6f675a9b2124d2f8  52abe1e300a8aa10  2b416f1d7e89ad3b  \n",
       "2       M3X  99a5f1ff7f3e54f0  e4c132d02ff6c095  ff71a556d86c4b8f  \n",
       "3  KNT-UL10  a8dc52f65085212e  e1c78a56cc9dfc8b  cf1527a0b4173e8f  \n",
       "4  IPHONE 5               NaN  abb6b4b8f15be6d6  cbc62c2b1cb7deb9  "
      ]
     },
     "execution_count": 180,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#删除地理信息，目前不会挖掘\n",
    "train_X_tr.drop('geo_code',axis = 1,inplace = True)\n",
    "#train_X_tr.drop('acc_id1_isnull',axis = 1,inplace = True)\n",
    "train_X_tr.head(5)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>UID</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>trans_amt</th>\n",
       "      <th>bal</th>\n",
       "      <th>acc_id1</th>\n",
       "      <th>acc_id2</th>\n",
       "      <th>acc_id3</th>\n",
       "      <th>amt_src1</th>\n",
       "      <th>amt_src2</th>\n",
       "      <th>trans_type2</th>\n",
       "      <th>trans_type1</th>\n",
       "      <th>market_code</th>\n",
       "      <th>market_type</th>\n",
       "      <th>merchant</th>\n",
       "      <th>code1</th>\n",
       "      <th>code2</th>\n",
       "      <th>channel</th>\n",
       "      <th>device_code1</th>\n",
       "      <th>device_code2</th>\n",
       "      <th>device_code3</th>\n",
       "      <th>device1</th>\n",
       "      <th>device2</th>\n",
       "      <th>mac1</th>\n",
       "      <th>ip1</th>\n",
       "      <th>ip1_sub</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19092</td>\n",
       "      <td>30</td>\n",
       "      <td>11:48:47</td>\n",
       "      <td>1459</td>\n",
       "      <td>1007</td>\n",
       "      <td>544dfdeedad0ae67</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>acdbdb842ac20f1e</td>\n",
       "      <td>9fefed0a981dcb7a</td>\n",
       "      <td>102.0</td>\n",
       "      <td>26bcf43a19df14c8</td>\n",
       "      <td>2ecf94369847c748</td>\n",
       "      <td>1.0</td>\n",
       "      <td>abc6bc660561e0eb</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>102</td>\n",
       "      <td>ffda8eaa413171cb</td>\n",
       "      <td>b36097d8a79e5b43</td>\n",
       "      <td>NaN</td>\n",
       "      <td>d2cf44cec09806cc</td>\n",
       "      <td>VIVO X9L</td>\n",
       "      <td>7aaec0f23bfa60ea</td>\n",
       "      <td>a664530c1fb20abe</td>\n",
       "      <td>45f4ca1f4e9b9cb7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>13465</td>\n",
       "      <td>23</td>\n",
       "      <td>16:58:03</td>\n",
       "      <td>725</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4d7831c6f695ab19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>105.0</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7a87b1aa20972d48</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>140</td>\n",
       "      <td>0e305dafdd3af261</td>\n",
       "      <td>365ec16ad4006c4f</td>\n",
       "      <td>NaN</td>\n",
       "      <td>09baf2f39bc3dc86</td>\n",
       "      <td>NEM-AL10</td>\n",
       "      <td>6f675a9b2124d2f8</td>\n",
       "      <td>52abe1e300a8aa10</td>\n",
       "      <td>2b416f1d7e89ad3b</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>13713</td>\n",
       "      <td>22</td>\n",
       "      <td>09:56:39</td>\n",
       "      <td>127</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c5fc631370cabc0d</td>\n",
       "      <td>NaN</td>\n",
       "      <td>105.0</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>cfd035fc7e0a53b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>140</td>\n",
       "      <td>429d5656ba8f3d01</td>\n",
       "      <td>760cfbfc0c2e3b49</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a92470e4f878a3f4</td>\n",
       "      <td>M3X</td>\n",
       "      <td>99a5f1ff7f3e54f0</td>\n",
       "      <td>e4c132d02ff6c095</td>\n",
       "      <td>ff71a556d86c4b8f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>22703</td>\n",
       "      <td>1</td>\n",
       "      <td>18:11:45</td>\n",
       "      <td>99317</td>\n",
       "      <td>100</td>\n",
       "      <td>516e596377b2019c</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a571c7fda8b7df37</td>\n",
       "      <td>fbf6bf3c8927414c</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>c71c876b8979028e</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>140</td>\n",
       "      <td>609954adce541306</td>\n",
       "      <td>31989e264685a18c</td>\n",
       "      <td>NaN</td>\n",
       "      <td>09baf2f39bc3dc86</td>\n",
       "      <td>KNT-UL10</td>\n",
       "      <td>a8dc52f65085212e</td>\n",
       "      <td>e1c78a56cc9dfc8b</td>\n",
       "      <td>cf1527a0b4173e8f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>17816</td>\n",
       "      <td>22</td>\n",
       "      <td>13:04:02</td>\n",
       "      <td>3361</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c5fc631370cabc0d</td>\n",
       "      <td>NaN</td>\n",
       "      <td>105.0</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6628f5ca013e3582</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>140</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2f61e8f52151bd8b</td>\n",
       "      <td>aca4977fbe8741e1</td>\n",
       "      <td>IPHONE 5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>abb6b4b8f15be6d6</td>\n",
       "      <td>cbc62c2b1cb7deb9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     UID  day      time  trans_amt   bal           acc_id1 acc_id2 acc_id3  \\\n",
       "0  19092   30  11:48:47       1459  1007  544dfdeedad0ae67     NaN     NaN   \n",
       "1  13465   23  16:58:03        725   100               NaN     NaN     NaN   \n",
       "2  13713   22  09:56:39        127   100               NaN     NaN     NaN   \n",
       "3  22703    1  18:11:45      99317   100  516e596377b2019c     NaN     NaN   \n",
       "4  17816   22  13:04:02       3361   100               NaN     NaN     NaN   \n",
       "\n",
       "           amt_src1          amt_src2  trans_type2       trans_type1  \\\n",
       "0  acdbdb842ac20f1e  9fefed0a981dcb7a        102.0  26bcf43a19df14c8   \n",
       "1  4d7831c6f695ab19               NaN        105.0  c2f2023d279665b2   \n",
       "2  c5fc631370cabc0d               NaN        105.0  c2f2023d279665b2   \n",
       "3  a571c7fda8b7df37  fbf6bf3c8927414c          NaN  c2f2023d279665b2   \n",
       "4  c5fc631370cabc0d               NaN        105.0  c2f2023d279665b2   \n",
       "\n",
       "        market_code  market_type          merchant code1 code2  channel  \\\n",
       "0  2ecf94369847c748          1.0  abc6bc660561e0eb   NaN   NaN      102   \n",
       "1               NaN          0.0  7a87b1aa20972d48   NaN   NaN      140   \n",
       "2               NaN          0.0  cfd035fc7e0a53b2   NaN   NaN      140   \n",
       "3               NaN          0.0  c71c876b8979028e   NaN   NaN      140   \n",
       "4               NaN          0.0  6628f5ca013e3582   NaN   NaN      140   \n",
       "\n",
       "       device_code1      device_code2      device_code3           device1  \\\n",
       "0  ffda8eaa413171cb  b36097d8a79e5b43               NaN  d2cf44cec09806cc   \n",
       "1  0e305dafdd3af261  365ec16ad4006c4f               NaN  09baf2f39bc3dc86   \n",
       "2  429d5656ba8f3d01  760cfbfc0c2e3b49               NaN  a92470e4f878a3f4   \n",
       "3  609954adce541306  31989e264685a18c               NaN  09baf2f39bc3dc86   \n",
       "4               NaN               NaN  2f61e8f52151bd8b  aca4977fbe8741e1   \n",
       "\n",
       "    device2              mac1               ip1           ip1_sub  \n",
       "0  VIVO X9L  7aaec0f23bfa60ea  a664530c1fb20abe  45f4ca1f4e9b9cb7  \n",
       "1  NEM-AL10  6f675a9b2124d2f8  52abe1e300a8aa10  2b416f1d7e89ad3b  \n",
       "2       M3X  99a5f1ff7f3e54f0  e4c132d02ff6c095  ff71a556d86c4b8f  \n",
       "3  KNT-UL10  a8dc52f65085212e  e1c78a56cc9dfc8b  cf1527a0b4173e8f  \n",
       "4  IPHONE 5               NaN  abb6b4b8f15be6d6  cbc62c2b1cb7deb9  "
      ]
     },
     "execution_count": 181,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#选取做因子化\n",
    "##amt_src1 交易类型，余额，花呗做因子化\n",
    "##trans_type2\t线上线下 ，一定要因子化，只有4中，加上none,5中\n",
    "##market_type\t，营销类型，只有2种，加上空值，三种，一定要因子化\n",
    "##channel 平台，渠道，5种，加上空值6种，适合因子化\n",
    "values={'market_type':0}\n",
    "train_X_tr.fillna(value=values,inplace = True)\n",
    "train_X_tr.head(5)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [],
   "source": [
    "#对market_type因子化\n",
    "train_X_tr['market_type'], uniques =pd.factorize(train_X_tr['market_type'],sort=True)\n",
    "uniques\n",
    "del uniques"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>market_type_0</th>\n",
       "      <th>market_type_1</th>\n",
       "      <th>market_type_2</th>\n",
       "      <th>UID</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>trans_amt</th>\n",
       "      <th>bal</th>\n",
       "      <th>acc_id1</th>\n",
       "      <th>acc_id2</th>\n",
       "      <th>acc_id3</th>\n",
       "      <th>amt_src1</th>\n",
       "      <th>amt_src2</th>\n",
       "      <th>trans_type2</th>\n",
       "      <th>trans_type1</th>\n",
       "      <th>market_code</th>\n",
       "      <th>merchant</th>\n",
       "      <th>code1</th>\n",
       "      <th>code2</th>\n",
       "      <th>channel</th>\n",
       "      <th>device_code1</th>\n",
       "      <th>device_code2</th>\n",
       "      <th>device_code3</th>\n",
       "      <th>device1</th>\n",
       "      <th>device2</th>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4d7831c6f695ab19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>105.0</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7a87b1aa20972d48</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>140</td>\n",
       "      <td>0e305dafdd3af261</td>\n",
       "      <td>365ec16ad4006c4f</td>\n",
       "      <td>NaN</td>\n",
       "      <td>09baf2f39bc3dc86</td>\n",
       "      <td>NEM-AL10</td>\n",
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       "      <td>52abe1e300a8aa10</td>\n",
       "      <td>2b416f1d7e89ad3b</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13713</td>\n",
       "      <td>22</td>\n",
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       "      <td>127</td>\n",
       "      <td>100</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c5fc631370cabc0d</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>c2f2023d279665b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>cfd035fc7e0a53b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>140</td>\n",
       "      <td>429d5656ba8f3d01</td>\n",
       "      <td>760cfbfc0c2e3b49</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>M3X</td>\n",
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       "      <td>e4c132d02ff6c095</td>\n",
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       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "      <td>1</td>\n",
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       "      <td>99317</td>\n",
       "      <td>100</td>\n",
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       "      <td>140</td>\n",
       "      <td>609954adce541306</td>\n",
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       "      <td>cf1527a0b4173e8f</td>\n",
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       "      <th>4</th>\n",
       "      <td>1</td>\n",
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       "      <td>22</td>\n",
       "      <td>13:04:02</td>\n",
       "      <td>3361</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c5fc631370cabc0d</td>\n",
       "      <td>NaN</td>\n",
       "      <td>105.0</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6628f5ca013e3582</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>140</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2f61e8f52151bd8b</td>\n",
       "      <td>aca4977fbe8741e1</td>\n",
       "      <td>IPHONE 5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>abb6b4b8f15be6d6</td>\n",
       "      <td>cbc62c2b1cb7deb9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   market_type_0  market_type_1  market_type_2    UID  day      time  \\\n",
       "0              0              1              0  19092   30  11:48:47   \n",
       "1              1              0              0  13465   23  16:58:03   \n",
       "2              1              0              0  13713   22  09:56:39   \n",
       "3              1              0              0  22703    1  18:11:45   \n",
       "4              1              0              0  17816   22  13:04:02   \n",
       "\n",
       "   trans_amt   bal           acc_id1 acc_id2 acc_id3          amt_src1  \\\n",
       "0       1459  1007  544dfdeedad0ae67     NaN     NaN  acdbdb842ac20f1e   \n",
       "1        725   100               NaN     NaN     NaN  4d7831c6f695ab19   \n",
       "2        127   100               NaN     NaN     NaN  c5fc631370cabc0d   \n",
       "3      99317   100  516e596377b2019c     NaN     NaN  a571c7fda8b7df37   \n",
       "4       3361   100               NaN     NaN     NaN  c5fc631370cabc0d   \n",
       "\n",
       "           amt_src2  trans_type2       trans_type1       market_code  \\\n",
       "0  9fefed0a981dcb7a        102.0  26bcf43a19df14c8  2ecf94369847c748   \n",
       "1               NaN        105.0  c2f2023d279665b2               NaN   \n",
       "2               NaN        105.0  c2f2023d279665b2               NaN   \n",
       "3  fbf6bf3c8927414c          NaN  c2f2023d279665b2               NaN   \n",
       "4               NaN        105.0  c2f2023d279665b2               NaN   \n",
       "\n",
       "           merchant code1 code2  channel      device_code1      device_code2  \\\n",
       "0  abc6bc660561e0eb   NaN   NaN      102  ffda8eaa413171cb  b36097d8a79e5b43   \n",
       "1  7a87b1aa20972d48   NaN   NaN      140  0e305dafdd3af261  365ec16ad4006c4f   \n",
       "2  cfd035fc7e0a53b2   NaN   NaN      140  429d5656ba8f3d01  760cfbfc0c2e3b49   \n",
       "3  c71c876b8979028e   NaN   NaN      140  609954adce541306  31989e264685a18c   \n",
       "4  6628f5ca013e3582   NaN   NaN      140               NaN               NaN   \n",
       "\n",
       "       device_code3           device1   device2              mac1  \\\n",
       "0               NaN  d2cf44cec09806cc  VIVO X9L  7aaec0f23bfa60ea   \n",
       "1               NaN  09baf2f39bc3dc86  NEM-AL10  6f675a9b2124d2f8   \n",
       "2               NaN  a92470e4f878a3f4       M3X  99a5f1ff7f3e54f0   \n",
       "3               NaN  09baf2f39bc3dc86  KNT-UL10  a8dc52f65085212e   \n",
       "4  2f61e8f52151bd8b  aca4977fbe8741e1  IPHONE 5               NaN   \n",
       "\n",
       "                ip1           ip1_sub  \n",
       "0  a664530c1fb20abe  45f4ca1f4e9b9cb7  \n",
       "1  52abe1e300a8aa10  2b416f1d7e89ad3b  \n",
       "2  e4c132d02ff6c095  ff71a556d86c4b8f  \n",
       "3  e1c78a56cc9dfc8b  cf1527a0b4173e8f  \n",
       "4  abb6b4b8f15be6d6  cbc62c2b1cb7deb9  "
      ]
     },
     "execution_count": 183,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_X_tr.head(5)\n",
    "columns=list(train_X_tr.columns)\n",
    "columns.remove('market_type')\n",
    "columns_del_market_type=columns\n",
    "train_X_tr=pd.get_dummies(train_X_tr['market_type'],prefix='market_type').join(train_X_tr[columns_del_market_type])\n",
    "train_X_tr.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {},
   "outputs": [
    {
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13465</td>\n",
       "      <td>23</td>\n",
       "      <td>16:58:03</td>\n",
       "      <td>725</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4d7831c6f695ab19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>105.0</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7a87b1aa20972d48</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0e305dafdd3af261</td>\n",
       "      <td>365ec16ad4006c4f</td>\n",
       "      <td>NaN</td>\n",
       "      <td>09baf2f39bc3dc86</td>\n",
       "      <td>NEM-AL10</td>\n",
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       "      <td>2b416f1d7e89ad3b</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>0</td>\n",
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       "      <td>09:56:39</td>\n",
       "      <td>127</td>\n",
       "      <td>100</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c5fc631370cabc0d</td>\n",
       "      <td>NaN</td>\n",
       "      <td>105.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>cfd035fc7e0a53b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>429d5656ba8f3d01</td>\n",
       "      <td>760cfbfc0c2e3b49</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>e4c132d02ff6c095</td>\n",
       "      <td>ff71a556d86c4b8f</td>\n",
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       "      <td>18:11:45</td>\n",
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       "      <td>100</td>\n",
       "      <td>516e596377b2019c</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a571c7fda8b7df37</td>\n",
       "      <td>fbf6bf3c8927414c</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c71c876b8979028e</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>609954adce541306</td>\n",
       "      <td>31989e264685a18c</td>\n",
       "      <td>NaN</td>\n",
       "      <td>09baf2f39bc3dc86</td>\n",
       "      <td>KNT-UL10</td>\n",
       "      <td>a8dc52f65085212e</td>\n",
       "      <td>e1c78a56cc9dfc8b</td>\n",
       "      <td>cf1527a0b4173e8f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17816</td>\n",
       "      <td>22</td>\n",
       "      <td>13:04:02</td>\n",
       "      <td>3361</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c5fc631370cabc0d</td>\n",
       "      <td>NaN</td>\n",
       "      <td>105.0</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6628f5ca013e3582</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2f61e8f52151bd8b</td>\n",
       "      <td>aca4977fbe8741e1</td>\n",
       "      <td>IPHONE 5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>abb6b4b8f15be6d6</td>\n",
       "      <td>cbc62c2b1cb7deb9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   channel_102  channel_106  channel_118  channel_119  channel_140  \\\n",
       "0            1            0            0            0            0   \n",
       "1            0            0            0            0            1   \n",
       "2            0            0            0            0            1   \n",
       "3            0            0            0            0            1   \n",
       "4            0            0            0            0            1   \n",
       "\n",
       "   market_type_0  market_type_1  market_type_2    UID  day      time  \\\n",
       "0              0              1              0  19092   30  11:48:47   \n",
       "1              1              0              0  13465   23  16:58:03   \n",
       "2              1              0              0  13713   22  09:56:39   \n",
       "3              1              0              0  22703    1  18:11:45   \n",
       "4              1              0              0  17816   22  13:04:02   \n",
       "\n",
       "   trans_amt   bal           acc_id1 acc_id2 acc_id3          amt_src1  \\\n",
       "0       1459  1007  544dfdeedad0ae67     NaN     NaN  acdbdb842ac20f1e   \n",
       "1        725   100               NaN     NaN     NaN  4d7831c6f695ab19   \n",
       "2        127   100               NaN     NaN     NaN  c5fc631370cabc0d   \n",
       "3      99317   100  516e596377b2019c     NaN     NaN  a571c7fda8b7df37   \n",
       "4       3361   100               NaN     NaN     NaN  c5fc631370cabc0d   \n",
       "\n",
       "           amt_src2  trans_type2       trans_type1       market_code  \\\n",
       "0  9fefed0a981dcb7a        102.0  26bcf43a19df14c8  2ecf94369847c748   \n",
       "1               NaN        105.0  c2f2023d279665b2               NaN   \n",
       "2               NaN        105.0  c2f2023d279665b2               NaN   \n",
       "3  fbf6bf3c8927414c          NaN  c2f2023d279665b2               NaN   \n",
       "4               NaN        105.0  c2f2023d279665b2               NaN   \n",
       "\n",
       "           merchant code1 code2      device_code1      device_code2  \\\n",
       "0  abc6bc660561e0eb   NaN   NaN  ffda8eaa413171cb  b36097d8a79e5b43   \n",
       "1  7a87b1aa20972d48   NaN   NaN  0e305dafdd3af261  365ec16ad4006c4f   \n",
       "2  cfd035fc7e0a53b2   NaN   NaN  429d5656ba8f3d01  760cfbfc0c2e3b49   \n",
       "3  c71c876b8979028e   NaN   NaN  609954adce541306  31989e264685a18c   \n",
       "4  6628f5ca013e3582   NaN   NaN               NaN               NaN   \n",
       "\n",
       "       device_code3           device1   device2              mac1  \\\n",
       "0               NaN  d2cf44cec09806cc  VIVO X9L  7aaec0f23bfa60ea   \n",
       "1               NaN  09baf2f39bc3dc86  NEM-AL10  6f675a9b2124d2f8   \n",
       "2               NaN  a92470e4f878a3f4       M3X  99a5f1ff7f3e54f0   \n",
       "3               NaN  09baf2f39bc3dc86  KNT-UL10  a8dc52f65085212e   \n",
       "4  2f61e8f52151bd8b  aca4977fbe8741e1  IPHONE 5               NaN   \n",
       "\n",
       "                ip1           ip1_sub  \n",
       "0  a664530c1fb20abe  45f4ca1f4e9b9cb7  \n",
       "1  52abe1e300a8aa10  2b416f1d7e89ad3b  \n",
       "2  e4c132d02ff6c095  ff71a556d86c4b8f  \n",
       "3  e1c78a56cc9dfc8b  cf1527a0b4173e8f  \n",
       "4  abb6b4b8f15be6d6  cbc62c2b1cb7deb9  "
      ]
     },
     "execution_count": 184,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "values={'channel':0}\n",
    "train_X_tr.fillna(value=values,inplace = True)\n",
    "train_X_tr.head(5)\n",
    "\n",
    "columns=list(train_X_tr.columns)\n",
    "columns.remove('channel')\n",
    "columns_del_channel=columns\n",
    "train_X_tr=pd.get_dummies(train_X_tr['channel'],prefix='channel').join(train_X_tr[columns_del_channel])\n",
    "train_X_tr.head(5)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>trans_type2_0.0</th>\n",
       "      <th>trans_type2_102.0</th>\n",
       "      <th>trans_type2_103.0</th>\n",
       "      <th>trans_type2_104.0</th>\n",
       "      <th>trans_type2_105.0</th>\n",
       "      <th>channel_102</th>\n",
       "      <th>channel_106</th>\n",
       "      <th>channel_118</th>\n",
       "      <th>channel_119</th>\n",
       "      <th>channel_140</th>\n",
       "      <th>market_type_0</th>\n",
       "      <th>market_type_1</th>\n",
       "      <th>market_type_2</th>\n",
       "      <th>UID</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>trans_amt</th>\n",
       "      <th>bal</th>\n",
       "      <th>acc_id1</th>\n",
       "      <th>acc_id2</th>\n",
       "      <th>acc_id3</th>\n",
       "      <th>amt_src1</th>\n",
       "      <th>amt_src2</th>\n",
       "      <th>trans_type1</th>\n",
       "      <th>market_code</th>\n",
       "      <th>merchant</th>\n",
       "      <th>code1</th>\n",
       "      <th>code2</th>\n",
       "      <th>device_code1</th>\n",
       "      <th>device_code2</th>\n",
       "      <th>device_code3</th>\n",
       "      <th>device1</th>\n",
       "      <th>device2</th>\n",
       "      <th>mac1</th>\n",
       "      <th>ip1</th>\n",
       "      <th>ip1_sub</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>19092</td>\n",
       "      <td>30</td>\n",
       "      <td>11:48:47</td>\n",
       "      <td>1459</td>\n",
       "      <td>1007</td>\n",
       "      <td>544dfdeedad0ae67</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>acdbdb842ac20f1e</td>\n",
       "      <td>9fefed0a981dcb7a</td>\n",
       "      <td>26bcf43a19df14c8</td>\n",
       "      <td>2ecf94369847c748</td>\n",
       "      <td>abc6bc660561e0eb</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ffda8eaa413171cb</td>\n",
       "      <td>b36097d8a79e5b43</td>\n",
       "      <td>NaN</td>\n",
       "      <td>d2cf44cec09806cc</td>\n",
       "      <td>VIVO X9L</td>\n",
       "      <td>7aaec0f23bfa60ea</td>\n",
       "      <td>a664530c1fb20abe</td>\n",
       "      <td>45f4ca1f4e9b9cb7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13465</td>\n",
       "      <td>23</td>\n",
       "      <td>16:58:03</td>\n",
       "      <td>725</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4d7831c6f695ab19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7a87b1aa20972d48</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0e305dafdd3af261</td>\n",
       "      <td>365ec16ad4006c4f</td>\n",
       "      <td>NaN</td>\n",
       "      <td>09baf2f39bc3dc86</td>\n",
       "      <td>NEM-AL10</td>\n",
       "      <td>6f675a9b2124d2f8</td>\n",
       "      <td>52abe1e300a8aa10</td>\n",
       "      <td>2b416f1d7e89ad3b</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13713</td>\n",
       "      <td>22</td>\n",
       "      <td>09:56:39</td>\n",
       "      <td>127</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c5fc631370cabc0d</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>cfd035fc7e0a53b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>429d5656ba8f3d01</td>\n",
       "      <td>760cfbfc0c2e3b49</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a92470e4f878a3f4</td>\n",
       "      <td>M3X</td>\n",
       "      <td>99a5f1ff7f3e54f0</td>\n",
       "      <td>e4c132d02ff6c095</td>\n",
       "      <td>ff71a556d86c4b8f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>22703</td>\n",
       "      <td>1</td>\n",
       "      <td>18:11:45</td>\n",
       "      <td>99317</td>\n",
       "      <td>100</td>\n",
       "      <td>516e596377b2019c</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a571c7fda8b7df37</td>\n",
       "      <td>fbf6bf3c8927414c</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c71c876b8979028e</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>609954adce541306</td>\n",
       "      <td>31989e264685a18c</td>\n",
       "      <td>NaN</td>\n",
       "      <td>09baf2f39bc3dc86</td>\n",
       "      <td>KNT-UL10</td>\n",
       "      <td>a8dc52f65085212e</td>\n",
       "      <td>e1c78a56cc9dfc8b</td>\n",
       "      <td>cf1527a0b4173e8f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17816</td>\n",
       "      <td>22</td>\n",
       "      <td>13:04:02</td>\n",
       "      <td>3361</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c5fc631370cabc0d</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c2f2023d279665b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6628f5ca013e3582</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2f61e8f52151bd8b</td>\n",
       "      <td>aca4977fbe8741e1</td>\n",
       "      <td>IPHONE 5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>abb6b4b8f15be6d6</td>\n",
       "      <td>cbc62c2b1cb7deb9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   trans_type2_0.0  trans_type2_102.0  trans_type2_103.0  trans_type2_104.0  \\\n",
       "0                0                  1                  0                  0   \n",
       "1                0                  0                  0                  0   \n",
       "2                0                  0                  0                  0   \n",
       "3                1                  0                  0                  0   \n",
       "4                0                  0                  0                  0   \n",
       "\n",
       "   trans_type2_105.0  channel_102  channel_106  channel_118  channel_119  \\\n",
       "0                  0            1            0            0            0   \n",
       "1                  1            0            0            0            0   \n",
       "2                  1            0            0            0            0   \n",
       "3                  0            0            0            0            0   \n",
       "4                  1            0            0            0            0   \n",
       "\n",
       "   channel_140  market_type_0  market_type_1  market_type_2    UID  day  \\\n",
       "0            0              0              1              0  19092   30   \n",
       "1            1              1              0              0  13465   23   \n",
       "2            1              1              0              0  13713   22   \n",
       "3            1              1              0              0  22703    1   \n",
       "4            1              1              0              0  17816   22   \n",
       "\n",
       "       time  trans_amt   bal           acc_id1 acc_id2 acc_id3  \\\n",
       "0  11:48:47       1459  1007  544dfdeedad0ae67     NaN     NaN   \n",
       "1  16:58:03        725   100               NaN     NaN     NaN   \n",
       "2  09:56:39        127   100               NaN     NaN     NaN   \n",
       "3  18:11:45      99317   100  516e596377b2019c     NaN     NaN   \n",
       "4  13:04:02       3361   100               NaN     NaN     NaN   \n",
       "\n",
       "           amt_src1          amt_src2       trans_type1       market_code  \\\n",
       "0  acdbdb842ac20f1e  9fefed0a981dcb7a  26bcf43a19df14c8  2ecf94369847c748   \n",
       "1  4d7831c6f695ab19               NaN  c2f2023d279665b2               NaN   \n",
       "2  c5fc631370cabc0d               NaN  c2f2023d279665b2               NaN   \n",
       "3  a571c7fda8b7df37  fbf6bf3c8927414c  c2f2023d279665b2               NaN   \n",
       "4  c5fc631370cabc0d               NaN  c2f2023d279665b2               NaN   \n",
       "\n",
       "           merchant code1 code2      device_code1      device_code2  \\\n",
       "0  abc6bc660561e0eb   NaN   NaN  ffda8eaa413171cb  b36097d8a79e5b43   \n",
       "1  7a87b1aa20972d48   NaN   NaN  0e305dafdd3af261  365ec16ad4006c4f   \n",
       "2  cfd035fc7e0a53b2   NaN   NaN  429d5656ba8f3d01  760cfbfc0c2e3b49   \n",
       "3  c71c876b8979028e   NaN   NaN  609954adce541306  31989e264685a18c   \n",
       "4  6628f5ca013e3582   NaN   NaN               NaN               NaN   \n",
       "\n",
       "       device_code3           device1   device2              mac1  \\\n",
       "0               NaN  d2cf44cec09806cc  VIVO X9L  7aaec0f23bfa60ea   \n",
       "1               NaN  09baf2f39bc3dc86  NEM-AL10  6f675a9b2124d2f8   \n",
       "2               NaN  a92470e4f878a3f4       M3X  99a5f1ff7f3e54f0   \n",
       "3               NaN  09baf2f39bc3dc86  KNT-UL10  a8dc52f65085212e   \n",
       "4  2f61e8f52151bd8b  aca4977fbe8741e1  IPHONE 5               NaN   \n",
       "\n",
       "                ip1           ip1_sub  \n",
       "0  a664530c1fb20abe  45f4ca1f4e9b9cb7  \n",
       "1  52abe1e300a8aa10  2b416f1d7e89ad3b  \n",
       "2  e4c132d02ff6c095  ff71a556d86c4b8f  \n",
       "3  e1c78a56cc9dfc8b  cf1527a0b4173e8f  \n",
       "4  abb6b4b8f15be6d6  cbc62c2b1cb7deb9  "
      ]
     },
     "execution_count": 185,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "values={'trans_type2':0}\n",
    "train_X_tr.fillna(value=values,inplace = True)\n",
    "train_X_tr.head(5)\n",
    "\n",
    "columns=list(train_X_tr.columns)\n",
    "columns.remove('trans_type2')\n",
    "columns_del_trans_type2=columns\n",
    "train_X_tr=pd.get_dummies(train_X_tr['trans_type2'],prefix='trans_type2').join(train_X_tr[columns_del_trans_type2])\n",
    "train_X_tr.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>trans_type1_0</th>\n",
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       "      <td>1</td>\n",
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       "      <td>a571c7fda8b7df37</td>\n",
       "      <td>fbf6bf3c8927414c</td>\n",
       "      <td>8</td>\n",
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       "      <td>c71c876b8979028e</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>609954adce541306</td>\n",
       "      <td>31989e264685a18c</td>\n",
       "      <td>NaN</td>\n",
       "      <td>09baf2f39bc3dc86</td>\n",
       "      <td>KNT-UL10</td>\n",
       "      <td>a8dc52f65085212e</td>\n",
       "      <td>e1c78a56cc9dfc8b</td>\n",
       "      <td>cf1527a0b4173e8f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17816</td>\n",
       "      <td>22</td>\n",
       "      <td>13:04:02</td>\n",
       "      <td>3361</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c5fc631370cabc0d</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6628f5ca013e3582</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>2f61e8f52151bd8b</td>\n",
       "      <td>aca4977fbe8741e1</td>\n",
       "      <td>IPHONE 5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>abb6b4b8f15be6d6</td>\n",
       "      <td>cbc62c2b1cb7deb9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   trans_type1_0  trans_type1_1  trans_type1_2  trans_type1_3  trans_type1_4  \\\n",
       "0              1              0              0              0              0   \n",
       "1              0              0              0              0              0   \n",
       "2              0              0              0              0              0   \n",
       "3              0              0              0              0              0   \n",
       "4              0              0              0              0              0   \n",
       "\n",
       "   trans_type1_5  trans_type1_6  trans_type1_7  trans_type1_8  trans_type1_9  \\\n",
       "0              0              0              0              0              0   \n",
       "1              0              0              0              1              0   \n",
       "2              0              0              0              1              0   \n",
       "3              0              0              0              1              0   \n",
       "4              0              0              0              1              0   \n",
       "\n",
       "   trans_type1_10  trans_type1_11  trans_type1_12  trans_type1_13  \\\n",
       "0               0               0               0               0   \n",
       "1               0               0               0               0   \n",
       "2               0               0               0               0   \n",
       "3               0               0               0               0   \n",
       "4               0               0               0               0   \n",
       "\n",
       "   trans_type1_14  trans_type2_0.0  trans_type2_102.0  trans_type2_103.0  \\\n",
       "0               0                0                  1                  0   \n",
       "1               0                0                  0                  0   \n",
       "2               0                0                  0                  0   \n",
       "3               0                1                  0                  0   \n",
       "4               0                0                  0                  0   \n",
       "\n",
       "   trans_type2_104.0  trans_type2_105.0  channel_102  channel_106  \\\n",
       "0                  0                  0            1            0   \n",
       "1                  0                  1            0            0   \n",
       "2                  0                  1            0            0   \n",
       "3                  0                  0            0            0   \n",
       "4                  0                  1            0            0   \n",
       "\n",
       "   channel_118  channel_119  channel_140  market_type_0  market_type_1  \\\n",
       "0            0            0            0              0              1   \n",
       "1            0            0            1              1              0   \n",
       "2            0            0            1              1              0   \n",
       "3            0            0            1              1              0   \n",
       "4            0            0            1              1              0   \n",
       "\n",
       "   market_type_2    UID  day      time  trans_amt   bal           acc_id1  \\\n",
       "0              0  19092   30  11:48:47       1459  1007  544dfdeedad0ae67   \n",
       "1              0  13465   23  16:58:03        725   100               NaN   \n",
       "2              0  13713   22  09:56:39        127   100               NaN   \n",
       "3              0  22703    1  18:11:45      99317   100  516e596377b2019c   \n",
       "4              0  17816   22  13:04:02       3361   100               NaN   \n",
       "\n",
       "  acc_id2 acc_id3          amt_src1          amt_src2  trans_type1  \\\n",
       "0     NaN     NaN  acdbdb842ac20f1e  9fefed0a981dcb7a            0   \n",
       "1     NaN     NaN  4d7831c6f695ab19               NaN            8   \n",
       "2     NaN     NaN  c5fc631370cabc0d               NaN            8   \n",
       "3     NaN     NaN  a571c7fda8b7df37  fbf6bf3c8927414c            8   \n",
       "4     NaN     NaN  c5fc631370cabc0d               NaN            8   \n",
       "\n",
       "        market_code          merchant code1 code2      device_code1  \\\n",
       "0  2ecf94369847c748  abc6bc660561e0eb   NaN   NaN  ffda8eaa413171cb   \n",
       "1               NaN  7a87b1aa20972d48   NaN   NaN  0e305dafdd3af261   \n",
       "2               NaN  cfd035fc7e0a53b2   NaN   NaN  429d5656ba8f3d01   \n",
       "3               NaN  c71c876b8979028e   NaN   NaN  609954adce541306   \n",
       "4               NaN  6628f5ca013e3582   NaN   NaN               NaN   \n",
       "\n",
       "       device_code2      device_code3           device1   device2  \\\n",
       "0  b36097d8a79e5b43               NaN  d2cf44cec09806cc  VIVO X9L   \n",
       "1  365ec16ad4006c4f               NaN  09baf2f39bc3dc86  NEM-AL10   \n",
       "2  760cfbfc0c2e3b49               NaN  a92470e4f878a3f4       M3X   \n",
       "3  31989e264685a18c               NaN  09baf2f39bc3dc86  KNT-UL10   \n",
       "4               NaN  2f61e8f52151bd8b  aca4977fbe8741e1  IPHONE 5   \n",
       "\n",
       "               mac1               ip1           ip1_sub  \n",
       "0  7aaec0f23bfa60ea  a664530c1fb20abe  45f4ca1f4e9b9cb7  \n",
       "1  6f675a9b2124d2f8  52abe1e300a8aa10  2b416f1d7e89ad3b  \n",
       "2  99a5f1ff7f3e54f0  e4c132d02ff6c095  ff71a556d86c4b8f  \n",
       "3  a8dc52f65085212e  e1c78a56cc9dfc8b  cf1527a0b4173e8f  \n",
       "4               NaN  abb6b4b8f15be6d6  cbc62c2b1cb7deb9  "
      ]
     },
     "execution_count": 186,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "values={'trans_type1':'0'}\n",
    "train_X_tr.fillna(value=values,inplace = True)\n",
    "train_X_tr.head(5)\n",
    "\n",
    "train_X_tr['trans_type1'], uniques =pd.factorize(train_X_tr['trans_type1'],sort=True)\n",
    "uniques\n",
    "#del uniques\n",
    "\n",
    "columns=list(train_X_tr.columns)\n",
    "#columns.remove('trans_type1')\n",
    "#columns_del_trans_type1=columns\n",
    "#最好还保留因子化后的trans_type1，放在后面的groupby字段里，同时get_dummies(train_X_tr['trans_type1']得到这笔交易是什么类型\n",
    "train_X_tr=pd.get_dummies(train_X_tr['trans_type1'],prefix='trans_type1').join(train_X_tr[columns])\n",
    "train_X_tr.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>amt_src1_0</th>\n",
       "      <th>amt_src1_1</th>\n",
       "      <th>amt_src1_2</th>\n",
       "      <th>amt_src1_3</th>\n",
       "      <th>amt_src1_4</th>\n",
       "      <th>amt_src1_5</th>\n",
       "      <th>amt_src1_6</th>\n",
       "      <th>amt_src1_7</th>\n",
       "      <th>amt_src1_8</th>\n",
       "      <th>amt_src1_9</th>\n",
       "      <th>amt_src1_10</th>\n",
       "      <th>amt_src1_11</th>\n",
       "      <th>amt_src1_12</th>\n",
       "      <th>amt_src1_13</th>\n",
       "      <th>amt_src1_14</th>\n",
       "      <th>amt_src1_15</th>\n",
       "      <th>amt_src1_16</th>\n",
       "      <th>amt_src1_17</th>\n",
       "      <th>amt_src1_18</th>\n",
       "      <th>amt_src1_19</th>\n",
       "      <th>amt_src1_20</th>\n",
       "      <th>amt_src1_21</th>\n",
       "      <th>amt_src1_22</th>\n",
       "      <th>amt_src1_23</th>\n",
       "      <th>amt_src1_24</th>\n",
       "      <th>amt_src1_25</th>\n",
       "      <th>amt_src1_26</th>\n",
       "      <th>amt_src1_27</th>\n",
       "      <th>trans_type1_0</th>\n",
       "      <th>trans_type1_1</th>\n",
       "      <th>trans_type1_2</th>\n",
       "      <th>trans_type1_3</th>\n",
       "      <th>trans_type1_4</th>\n",
       "      <th>trans_type1_5</th>\n",
       "      <th>trans_type1_6</th>\n",
       "      <th>trans_type1_7</th>\n",
       "      <th>trans_type1_8</th>\n",
       "      <th>trans_type1_9</th>\n",
       "      <th>trans_type1_10</th>\n",
       "      <th>trans_type1_11</th>\n",
       "      <th>trans_type1_12</th>\n",
       "      <th>trans_type1_13</th>\n",
       "      <th>trans_type1_14</th>\n",
       "      <th>trans_type2_0.0</th>\n",
       "      <th>trans_type2_102.0</th>\n",
       "      <th>trans_type2_103.0</th>\n",
       "      <th>trans_type2_104.0</th>\n",
       "      <th>trans_type2_105.0</th>\n",
       "      <th>channel_102</th>\n",
       "      <th>channel_106</th>\n",
       "      <th>channel_118</th>\n",
       "      <th>channel_119</th>\n",
       "      <th>channel_140</th>\n",
       "      <th>market_type_0</th>\n",
       "      <th>market_type_1</th>\n",
       "      <th>market_type_2</th>\n",
       "      <th>UID</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>trans_amt</th>\n",
       "      <th>bal</th>\n",
       "      <th>acc_id1</th>\n",
       "      <th>acc_id2</th>\n",
       "      <th>acc_id3</th>\n",
       "      <th>amt_src1</th>\n",
       "      <th>amt_src2</th>\n",
       "      <th>trans_type1</th>\n",
       "      <th>market_code</th>\n",
       "      <th>merchant</th>\n",
       "      <th>code1</th>\n",
       "      <th>code2</th>\n",
       "      <th>device_code1</th>\n",
       "      <th>device_code2</th>\n",
       "      <th>device_code3</th>\n",
       "      <th>device1</th>\n",
       "      <th>device2</th>\n",
       "      <th>mac1</th>\n",
       "      <th>ip1</th>\n",
       "      <th>ip1_sub</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>19092</td>\n",
       "      <td>30</td>\n",
       "      <td>11:48:47</td>\n",
       "      <td>1459</td>\n",
       "      <td>1007</td>\n",
       "      <td>544dfdeedad0ae67</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18</td>\n",
       "      <td>9fefed0a981dcb7a</td>\n",
       "      <td>0</td>\n",
       "      <td>2ecf94369847c748</td>\n",
       "      <td>abc6bc660561e0eb</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ffda8eaa413171cb</td>\n",
       "      <td>b36097d8a79e5b43</td>\n",
       "      <td>NaN</td>\n",
       "      <td>d2cf44cec09806cc</td>\n",
       "      <td>VIVO X9L</td>\n",
       "      <td>7aaec0f23bfa60ea</td>\n",
       "      <td>a664530c1fb20abe</td>\n",
       "      <td>45f4ca1f4e9b9cb7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13465</td>\n",
       "      <td>23</td>\n",
       "      <td>16:58:03</td>\n",
       "      <td>725</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7a87b1aa20972d48</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0e305dafdd3af261</td>\n",
       "      <td>365ec16ad4006c4f</td>\n",
       "      <td>NaN</td>\n",
       "      <td>09baf2f39bc3dc86</td>\n",
       "      <td>NEM-AL10</td>\n",
       "      <td>6f675a9b2124d2f8</td>\n",
       "      <td>52abe1e300a8aa10</td>\n",
       "      <td>2b416f1d7e89ad3b</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>13713</td>\n",
       "      <td>22</td>\n",
       "      <td>09:56:39</td>\n",
       "      <td>127</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>cfd035fc7e0a53b2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>429d5656ba8f3d01</td>\n",
       "      <td>760cfbfc0c2e3b49</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a92470e4f878a3f4</td>\n",
       "      <td>M3X</td>\n",
       "      <td>99a5f1ff7f3e54f0</td>\n",
       "      <td>e4c132d02ff6c095</td>\n",
       "      <td>ff71a556d86c4b8f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>22703</td>\n",
       "      <td>1</td>\n",
       "      <td>18:11:45</td>\n",
       "      <td>99317</td>\n",
       "      <td>100</td>\n",
       "      <td>516e596377b2019c</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17</td>\n",
       "      <td>fbf6bf3c8927414c</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>c71c876b8979028e</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>609954adce541306</td>\n",
       "      <td>31989e264685a18c</td>\n",
       "      <td>NaN</td>\n",
       "      <td>09baf2f39bc3dc86</td>\n",
       "      <td>KNT-UL10</td>\n",
       "      <td>a8dc52f65085212e</td>\n",
       "      <td>e1c78a56cc9dfc8b</td>\n",
       "      <td>cf1527a0b4173e8f</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>17816</td>\n",
       "      <td>22</td>\n",
       "      <td>13:04:02</td>\n",
       "      <td>3361</td>\n",
       "      <td>100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6628f5ca013e3582</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2f61e8f52151bd8b</td>\n",
       "      <td>aca4977fbe8741e1</td>\n",
       "      <td>IPHONE 5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>abb6b4b8f15be6d6</td>\n",
       "      <td>cbc62c2b1cb7deb9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   amt_src1_0  amt_src1_1  amt_src1_2  amt_src1_3  amt_src1_4  amt_src1_5  \\\n",
       "0           0           0           0           0           0           0   \n",
       "1           0           0           0           0           0           0   \n",
       "2           0           0           0           0           0           0   \n",
       "3           0           0           0           0           0           0   \n",
       "4           0           0           0           0           0           0   \n",
       "\n",
       "   amt_src1_6  amt_src1_7  amt_src1_8  amt_src1_9  amt_src1_10  amt_src1_11  \\\n",
       "0           0           0           0           0            0            0   \n",
       "1           0           1           0           0            0            0   \n",
       "2           0           0           0           0            0            0   \n",
       "3           0           0           0           0            0            0   \n",
       "4           0           0           0           0            0            0   \n",
       "\n",
       "   amt_src1_12  amt_src1_13  amt_src1_14  amt_src1_15  amt_src1_16  \\\n",
       "0            0            0            0            0            0   \n",
       "1            0            0            0            0            0   \n",
       "2            0            0            0            0            0   \n",
       "3            0            0            0            0            0   \n",
       "4            0            0            0            0            0   \n",
       "\n",
       "   amt_src1_17  amt_src1_18  amt_src1_19  amt_src1_20  amt_src1_21  \\\n",
       "0            0            1            0            0            0   \n",
       "1            0            0            0            0            0   \n",
       "2            0            0            0            0            1   \n",
       "3            1            0            0            0            0   \n",
       "4            0            0            0            0            1   \n",
       "\n",
       "   amt_src1_22  amt_src1_23  amt_src1_24  amt_src1_25  amt_src1_26  \\\n",
       "0            0            0            0            0            0   \n",
       "1            0            0            0            0            0   \n",
       "2            0            0            0            0            0   \n",
       "3            0            0            0            0            0   \n",
       "4            0            0            0            0            0   \n",
       "\n",
       "   amt_src1_27  trans_type1_0  trans_type1_1  trans_type1_2  trans_type1_3  \\\n",
       "0            0              1              0              0              0   \n",
       "1            0              0              0              0              0   \n",
       "2            0              0              0              0              0   \n",
       "3            0              0              0              0              0   \n",
       "4            0              0              0              0              0   \n",
       "\n",
       "   trans_type1_4  trans_type1_5  trans_type1_6  trans_type1_7  trans_type1_8  \\\n",
       "0              0              0              0              0              0   \n",
       "1              0              0              0              0              1   \n",
       "2              0              0              0              0              1   \n",
       "3              0              0              0              0              1   \n",
       "4              0              0              0              0              1   \n",
       "\n",
       "   trans_type1_9  trans_type1_10  trans_type1_11  trans_type1_12  \\\n",
       "0              0               0               0               0   \n",
       "1              0               0               0               0   \n",
       "2              0               0               0               0   \n",
       "3              0               0               0               0   \n",
       "4              0               0               0               0   \n",
       "\n",
       "   trans_type1_13  trans_type1_14  trans_type2_0.0  trans_type2_102.0  \\\n",
       "0               0               0                0                  1   \n",
       "1               0               0                0                  0   \n",
       "2               0               0                0                  0   \n",
       "3               0               0                1                  0   \n",
       "4               0               0                0                  0   \n",
       "\n",
       "   trans_type2_103.0  trans_type2_104.0  trans_type2_105.0  channel_102  \\\n",
       "0                  0                  0                  0            1   \n",
       "1                  0                  0                  1            0   \n",
       "2                  0                  0                  1            0   \n",
       "3                  0                  0                  0            0   \n",
       "4                  0                  0                  1            0   \n",
       "\n",
       "   channel_106  channel_118  channel_119  channel_140  market_type_0  \\\n",
       "0            0            0            0            0              0   \n",
       "1            0            0            0            1              1   \n",
       "2            0            0            0            1              1   \n",
       "3            0            0            0            1              1   \n",
       "4            0            0            0            1              1   \n",
       "\n",
       "   market_type_1  market_type_2    UID  day      time  trans_amt   bal  \\\n",
       "0              1              0  19092   30  11:48:47       1459  1007   \n",
       "1              0              0  13465   23  16:58:03        725   100   \n",
       "2              0              0  13713   22  09:56:39        127   100   \n",
       "3              0              0  22703    1  18:11:45      99317   100   \n",
       "4              0              0  17816   22  13:04:02       3361   100   \n",
       "\n",
       "            acc_id1 acc_id2 acc_id3  amt_src1          amt_src2  trans_type1  \\\n",
       "0  544dfdeedad0ae67     NaN     NaN        18  9fefed0a981dcb7a            0   \n",
       "1               NaN     NaN     NaN         7               NaN            8   \n",
       "2               NaN     NaN     NaN        21               NaN            8   \n",
       "3  516e596377b2019c     NaN     NaN        17  fbf6bf3c8927414c            8   \n",
       "4               NaN     NaN     NaN        21               NaN            8   \n",
       "\n",
       "        market_code          merchant code1 code2      device_code1  \\\n",
       "0  2ecf94369847c748  abc6bc660561e0eb   NaN   NaN  ffda8eaa413171cb   \n",
       "1               NaN  7a87b1aa20972d48   NaN   NaN  0e305dafdd3af261   \n",
       "2               NaN  cfd035fc7e0a53b2   NaN   NaN  429d5656ba8f3d01   \n",
       "3               NaN  c71c876b8979028e   NaN   NaN  609954adce541306   \n",
       "4               NaN  6628f5ca013e3582   NaN   NaN               NaN   \n",
       "\n",
       "       device_code2      device_code3           device1   device2  \\\n",
       "0  b36097d8a79e5b43               NaN  d2cf44cec09806cc  VIVO X9L   \n",
       "1  365ec16ad4006c4f               NaN  09baf2f39bc3dc86  NEM-AL10   \n",
       "2  760cfbfc0c2e3b49               NaN  a92470e4f878a3f4       M3X   \n",
       "3  31989e264685a18c               NaN  09baf2f39bc3dc86  KNT-UL10   \n",
       "4               NaN  2f61e8f52151bd8b  aca4977fbe8741e1  IPHONE 5   \n",
       "\n",
       "               mac1               ip1           ip1_sub  \n",
       "0  7aaec0f23bfa60ea  a664530c1fb20abe  45f4ca1f4e9b9cb7  \n",
       "1  6f675a9b2124d2f8  52abe1e300a8aa10  2b416f1d7e89ad3b  \n",
       "2  99a5f1ff7f3e54f0  e4c132d02ff6c095  ff71a556d86c4b8f  \n",
       "3  a8dc52f65085212e  e1c78a56cc9dfc8b  cf1527a0b4173e8f  \n",
       "4               NaN  abb6b4b8f15be6d6  cbc62c2b1cb7deb9  "
      ]
     },
     "execution_count": 187,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "values={'amt_src1':'0'}\n",
    "train_X_tr.fillna(value=values,inplace = True)\n",
    "train_X_tr.head(5)\n",
    "\n",
    "train_X_tr['amt_src1'], uniques =pd.factorize(train_X_tr['amt_src1'],sort=True)\n",
    "uniques\n",
    "#del uniques\n",
    "\n",
    "columns=list(train_X_tr.columns)\n",
    "#columns.remove('amt_src1')\n",
    "#columns_del_amt_src1=columns\n",
    "#最好还保留因子化后的trans_type1，放在后面的groupby字段里，同时get_dummies(train_X_tr['amt_src1']得到这笔交易是什么类型\n",
    "train_X_tr=pd.get_dummies(train_X_tr['amt_src1'],prefix='amt_src1').join(train_X_tr[columns])\n",
    "train_X_tr.head(5)"
   ]
  }
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